G'MIC 1.7.1

When the flowers are blooming, image filters abound!

A new version 1.7.1 “Spring 2016” of G’MIC (GREYC’s Magic for Image Computing), the open-source framework for image processing, has been released recently (26 April 2016). This is a great opportunity to summarize some of the latest advances and features over the last 5 months.

G’MIC: A brief overview

G’MIC is an open-source project started in August 2008. It has been developed in the IMAGE team of the GREYC laboratory from the CNRS (one of the major French public research institutes). This team is made up of researchers and teachers specializing in the algorithms and mathematics of image processing. G’MIC is released under the free software licence CeCILL (GPL-compatible) for various platforms (Linux, Mac and Windows). It provides a set of various user interfaces for the manipulation of generic image data, that is images or image sequences of multispectral data being _2D_ or _3D_, and with high-bit precision (up to 32bits floats per channel). Of course, it manages “classical” color images as well.

Note that the project just got a redesign of its mascot Gmicky, drawn by David Revoy, a French illustrator well-known to free graphics lovers for being responsible for the great libre webcomics Pepper&Carott.

G’MIC is probably best known for it’s GIMP plug-in, first released in 2009. Today, this popular GIMP extension proposes more than 460 customizable filters and effects to apply on your images.

But G’MIC is not a plug-in for GIMP only. It also offers a command-line interface, that can be used in addition with the CLI tools from ImageMagick or GraphicsMagick (this is undoubtly the most powerful and flexible interface of the framework). G’MIC also has a web service G’MIC Online to apply effects on your images directly from a web browser. Other G’MIC-based interfaces also exist (ZArt, a plug-in for Krita, filters for Photoflow…). All these interfaces are based on the generic C++ libraries CImg and libgmic which are portable, thread-safe and multi-threaded (through the use of OpenMP). Today, G’MIC has more than 900 functions to process images, all being fully configurable, for a library of only approximately 150 kloc of source code. It’s features cover a wide spectrum of the image processing field, with algorithms for geometric and color manipulations, image filtering (denoising/sharpening with spectral, variational or patch-based approaches…), motion estimation and registration, drawing of graphic primitives (up to 3d vector objects), edge detection, object segmentation, artistic rendering, etc. This is a versatile tool, useful to visualize and explore complex image data, as well as elaborate custom image processing pipelines (see these slides to get more information about the motivations and goals of the G’MIC project).

A selection of some new filters and effects

Here we look at the descriptions of some of the most significant filters recently added. We illustrate their usage from the G’MIC plug-in for GIMP. All of these filters are of course available from other interfaces as well (in particular within the CLI tool gmic).

Painterly rendering of photographs

The filter Artistic / Brushify tries to transform an image into a painting. Here, the idea is to simulate the process of painting with brushes on a white canvas. One provides a template image and the algorithm first analyzes the image geometry (local contrasts and orientations of the contours), then attempt to reproduce the image with a single brush that will be locally rotated and scaled accordingly to the contour geometry. By simulating enough of brushstrokes, one gets a “painted” version of the template image, which is more or less close to the original one, depending on the brush shape, its size, the number of allowed orientations, etc. All these settings being customizable by the user as parameters of the algorithm: This filter allows thus to render a wide variety of painting effects.

The animation below illustrates the diversity of results one can get with this filter, applied on the same input picture of a lion. Various brush shapes and geometries have been supplied to the algorithm. Brushify is computationally expensive so its implementation is parallelized (each core gives several brushstrokes simultaneously).

Note that it’s particularly fun to invoke this filter from the command line interface (using the option -brushify available in gmic) to process a sequence of video frames (see this example of “ brushified “ video):

Reconstructing missing data from sparse samples

G’MIC gets a new algorithm to reconstruct missing data in images. This is a classical problem in image processing, often named “Image Inpainting“, and G’MIC already had a lot of useful filters to solve this problem. Here, the newly added interpolation method assumes only a sparse set of image data is known, for instance a few scattered pixels over the image (instead of continuous chuncks of image data). The analysis and the reconstruction of the global image geometry is then particularly tough.

The new option -solidify in G’MIC allows the reconstruction of dense image data from such a sparse sampling, based on a multi-scale diffusion PDE’s-based technique. The figure below illustrates the ability of the algorithm with an example of image reconstruction. We start from an input image of a waterdrop, and we keep only 2.7% of the image data (a very little amount of data!). The algorithm is able to reconstruct a whole image that looks like the input, even if all the small details have not been fully reconstructed (of course!). The more samples we have, the finer details we can recover.

As this reconstruction technique is quite generic, several new G’MIC filters takes advantage of it:

• Filter Repair / Solidify applies the algorithm in a direct manner, by reconstructing transparent areas from the interpolation of opaque regions. The animation below shows how this filter can be used to create an artistic blur on the image borders.

From an artistic point of view, there are many possibilities offered by this filters. For instance, it becomes really easy to generate color gradients with complex shapes, as shown with the two examples below (also in this video that details the whole process).

• Filter Artistic / Smooth abstract uses same idea as the one with the waterdrop image: it purposely sub-samples the image in a sparse way, by choosing keypoints mainly on the image edges, then use the reconstruction algorithm to get the image back. With a low number of samples, the filter can only render a piecewise smooth image, i.e. a smooth abstraction of the input image.

• Filter Rendering / Gradient [random] is able to synthetize random colored backgrounds. Here again, the filter initializes a set of colors keypoints randomly chosen over the image, then interpolate them with the new reconstruction algorithm. We end up with a psychedelic background composed of randomly oriented color gradients.

• Simulation of analog films : the new reconstruction algorithm also allowed a major improvement for all the analog film emulation filters that have been present in G’MIC for years. The section Film emulation/ proposes a wide variety of filters for this purpose. Their goal is to apply color transformations to simulate the look of a picture shot by an analogue camera with a certain kind of film. Below, you can see for instance a few of the 300 colorimetric transformations that are available in G’MIC.

From an algorithmic point of view, such a color mapping is extremely simple to implement : for each of the 300+ presets, G’MIC actually has an HaldCLUT, that is a function defining for each possible color (R,G,B) (of the original image), a new color (R’,G’,B’) color to set instead. As this function is not necessarily analytic, a HaldCLUT is stored in a discrete manner as a lookup table that gives the result of the mapping for all possible colors of the RGB cube (that is 2^24 = 16777216 values if we work with a 8bits precision per color component). This HaldCLUT-based color mapping is illustrated below for all values of the RGB color cube.

This is a large amount of data: even by subsampling the RGB space (e.g. with 6 bits per component) and compressing the corresponding HaldCLUT file, you ends up with approximately 200 and 300 kB for each mapping file. Multiply this number by 300+ (the number of available mappings in G’MIC), and you get a total of 85MB of data, to store all these color transformations. Definitely not convenient to spread and package!

The idea was then to develop a new lossy compression technique focused on HaldCLUT files, that is volumetric discretised vector-valued functions which are piecewise smooth by nature. And that what has been done in G’MIC, thanks to the new sparse reconstruction algorithm. Indeed, the reconstruction technique also works with _3D_ image data (such as a HaldCLUT!), so one simply has to extract a sufficient number of significant keypoints in the RGB cube and interpolate them afterwards to allow the reconstruction of a whole HaldCLUT (taking care to have a reconstruction error small enough to be sure that the color mapping we get with the compressed HaldCLUT is indistinguishable from the non-compressed one).

Thus, G’MIC doesn’t need to store all the color data from a HaldCLUT, but only a sparse sampling of it (i.e. a sequence of { rgb_keypoint, new_rgb_color }). Depending on the geometric complexity of the HaldCLUTs to encode, more or less keypoints are necessary (roughly from _30_ to 2000). As a result, the storage of the 300+ HaldCLUTs in G’MIC requires now only 850 KiB of data (instead of 85 MiB), that is a compression gain of 99% ! That makes the whole HaldCLUT data storable in a single file that is easy to ship with the G’MIC package. Now, a user can then apply all the G’MIC color transformations while being offline (previously, each HaldCLUT had to be downloaded separately from the G’MIC server when requested).

It looks like this new reconstruction algorithm from sparse samples is really great, and no doubts it will be used in other filters in the future.

Make textures tileable

Filter Arrays & tiles / Make seamless [patch-based] tries to transform an input texture to make it tileable, so that it can be duplicated as tiles along the horizontal and vertical axes without visible seams on the borders of adjacent tiles. Note that this is something that can be extremely hard to achieve, if the input texture has few auto-similarity or glaring luminosity changes spatially. That is the case for instance with the “Salmon” texture shown below as four adjacent tiles (configuration 2x2) with a lighting that goes from dark (on the left) to bright (on the right). Here, the algorithm modifies the texture so that the tiling shows no seams, but where the aspect of the original texture is preserved as much as possible (only the texture borders are modified).

We can imagine some great uses of this filter, for instance in video games, where texture tiling is common to render large virtual worlds.

Image decomposition into several levels of details

A “new” filter Details / Split details [wavelets] has been added to decompose an image into several levels of details. It is based on the so-called “à trous” wavelet decomposition. For those who already know the popular Wavelet Decompose plug-in for GIMP, there won’t be so much novelty here, as it is mainly the same kind of decomposition technique that has been implemented. Having it directly in G’MIC is still a great news: it offers now a preview of the different scales that will be computed, and the implementation is parallelized to take advantage of multiple cores.

The filter outputs several layers, so that each layer contains the details of the image at a given scale. All those layers blended together gives the original image back.

Thus, one can work on those output layers separately and modify the image details only for a given scale. There are a lot of applications for this kind of image decomposition, one of the most spectacular being the ability to retouch the skin in portraits : the flaws of the skin are indeed often present in layers with middle-sized scales, while the natural skin texture (the pores) are present in the fine details. By selectively removing the flaws while keeping the pores, the skin aspect stays natural after the retouch (see this wonderful link for a detailed tutorial about skin retouching techniques, with GIMP).

Image denoising based on “Patch-PCA”

G’MIC is also well known to offer a wide range of algorithms for image denoising and smoothing (currently more than a dozen). And he got one more ! Filter Repair / Smooth [patch-pca] proposed a new image denoising algorithm that is both efficient and computationally intensive (despite its multi-threaded implementation, you probably should avoid it on a machine with less than 8 cores…). In return, it sometimes does magic to suppress noise while preserving small details.

The “Droste” effect

The Droste effect (also known as “mise en abyme“ in art) is the effect of a picture appearing within itself recursively. To achieve this, a new filter Deformations / Continuous droste has been added into G’MIC. It’s actually a complete rewrite of the popular Mathmap’s Droste filter that has existed for years. Mathmap was a very popular plug-in for GIMP, but it seems to be not maintained anymore. The Droste effect was one of its most iconic and complex filter. Martin “Souphead”, one former user of Mathmap then took the bull by the horns and converted the complex code of this filter specifically into a G’MIC script, resulting in a parallelized implementation of the filter.

This filter allows all artistic delusions. For instance, it becomes trivial to create the result below in a few steps: create a selection around the clock, move it on a transparent background, run the Droste filter, et voilà!.

Equirectangular to nadir-zenith transformation

The filter Deformations / Equirectangular to nadir-zenith is another filter converted from Mathmap to G’MIC. It is specifically used for the processing of panoramas: it reconstructs both the Zenith and the Nadir regions of a panorama so that they can be easily modified (for instance to reconstruct missing parts), before being reprojected back into the input panorama.

Morgan Hardwood has wrote a quite detailled tutorial, here on pixls.us, about the reconstruction of missing parts in the Zenith/Nadir of an equirectangular panorama. Check it out!

Other various improvements

Finally, here are other highlights about the G’MIC project:

• Filter Rendering / Kitaoka Spin Illusion is another Mathmap filter converted to G’MIC by Martin “Souphead”. It generates a certain kind of optical illusions as shown below (close your eyes if you are epileptic!)

• Filter Colors / Color blindness transforms the colors of an image to simulate different types of color blindness. This can be very helpful to check the accessibility of a web site or a graphical document for colorblind people. The color transformations used here are the same as defined on Coblis, a website that proposes to apply this kind of simulation online. The G’MIC filter gives strictly identical results, but it ease the batch processing of several images at once.

• Since a few years now, G’MIC has its own parser of mathematical expression, a really convenient module to perform complex calculations when applying image filters This core feature gets new functionalities: the ability to manage variables that can be complex, vector or matrix-valued, but also the creation of user-defined mathematical functions. For instance, the classical rendering of the Mandelbrot fractal set (done by estimating the divergence of a sequence of complex numbers) can be implemented like this, directly on the command line:

  $ gmic 512,512,1,1,"c = 2.4*[x/w,y/h] - [1.8,1.2]; z = [0,0]; for (iter = 0, cabs(z)<=2 && ++iter<256, z = z**z + c); 6*iter" -map 7,2
  

This clearly enlarge the math evaluator ability, as you are not limited to scalar variables anymore. You can now create complex filters which are able to solve linear systems or compute eigenvalues/eigenvectors, and this, for each pixel of an input image. It’s a bit like having a micro-(micro!)-Octave inside G’MIC. Note that the Brushify filter described earlier uses these new features extensively. It’s also interesting to know that the G’MIC math expression evaluator has its own JIT compiler to achieve a fast evaluation of expressions when applied on thousands of image values simultaneously.

• Another great contribution has been proposed by Tobias Fleischer, with the creation of a new _C_ API to invoke the functions of the libgmic library (which is the library containing all the G’MIC features, initially available through a C++ API only). As the _C_ ABI is standardized (unlike C++), this basically means G’MIC can be interfaced more easily with languages other than C++. In the future, we can imagine the development of G’MIC APIs for languages such as Python for instance. Tobias is currently using this new _C_ API to develop G’MIC-based plug-ins compatible with the OpenFX standard. Those plug-ins should be usable indifferently in video editing software such as After effects, Sony Vegas Pro or Natron. This is still an on-going work though.

• Another contributor Robin “Starfall Robles” started to develop a Python script to provide some of the G’MIC filters directly in the Blender video sequence editor. This work is still in a early stage, but you can already apply different G’MIC effects on image sequences (see this video for a demonstration).

• You can find out G’MIC filters also in the opensource nonlinear video editor Flowblade, thanks to the hard work of Janne Liljeblad (Flowblade project leader). Here again, the goal is to allow the application of G’MIC effects and filters directly on image sequences, mainly for artistic purposes (as shown in this video or this one).

What’s next ?

As you see, the G’MIC project is doing well, with an active development and cool new features added months after months. You can find and use interfaces to G’MIC in more and more opensource software, as GIMP, Krita, Blender, Photoflow, Flowblade, Veejay, EKD and Natron in a near future (at least we hope so!).

At the same time, we can see more and more external resources available for G’MIC : tutorials, blog articles (here, here, here,…), or demonstration videos (here, here, here, here,…). This shows the project becoming more useful to users of opensource software for graphics and photography.

The development of version 1.7.2 already hit the ground running, so stay tuned and visit the official G’MIC forum on pixls.us to get more info about the project developement and get answers to your questions. Meanwhile, feel the power of free software for image processing!

Links:

• G’MIC home page
• G’MIC plug-in for GIMP
• Introduction to the CLI interface of G’MIC
• Technical reference documentation
• G’MIC 1.7.1 release article on linuxfr.org

Alan Jenkins introduces and reads a selection of the poems of Gerard Manley Hopkins.

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Adrian Tahourdin and Mika Ross-Southall dip their toes in Casanova's celebrated memoirs.Find out more: www.the-tis.co.uk

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Catharine Morris and Michael Caines take a look at the English essayist, best known for his Confessions of an English Opium-Eater.Find out more at the-tis.co.uk

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Post Libre Graphics Meeting

What a trip!

What a blast!

This trip report is long overdue, but I wanted to process some of my images to share with everyone before I posted.

It had been a couple of years since I had an opportunity to travel and meet with the GIMP team again (Leipzig was awesome) so I was really looking forward to this trip. I missed the opportunity to head up to the great white North for last years meeting in Toronto.

London Calling

I was going to attend the pre-LGM photowalk again this year so this time I decided to pack some bigger off-camera lighting modifiers for everyone to play with. Here’s a neat travelling photographer pro-tip: most airlines will let you carry on an umbrella as a “freebie” item. They just don’t specify that it has to be an umbrella to keep the rain off you. So I carried on my big Photek Softlighter II (luckily my light stands fit in my checked luggage). Just be sure not to leave it behind somewhere (which I was paranoid about for most of my trip). Luckily I was only changing planes in Atlanta.

A couple of (bad) movies and hours later I was in Heathrow. I figured it wouldn’t be much trouble getting through border control.

I may have been a little optimistic about that.

The Border Force agent was quite nice and super inquisitive. So much so that I actually began to worry at some point (I think I must have spent almost 20 minutes talking to her) that she might not let me in!

She kept asking what I was coming to London for and I kept trying to explain to her what a “Libre Graphics Meeting“ was. This was almost a tragic comedy. The idea of Free Software did not seem to compute to her and I was sorry I had even made the passing mention. Her attention then turned to my umbrella and photography. What was I there to photograph? Who? Why? (Come to think of it, I should start asking myself those same questions more often… It was an existential visit to the border control.)

In the end I think she got bored with my answers and figured that I was far too awkward to be a threat to anything. Which pretty much sums up my entire college dating life.

Photowalk

In what I hope will become a tradition we had our photowalk the day before LGM officially kicked off and we could not have asked for a better day of weather! It was partly cloudy and just gorgeous (pretty much the complete opposite to what I was expecting for London weather).

Furtherfield Commons

I want to thank Ruth Catlow (http://ruthcatlow.net/) for allowing us to use the awesome space at Furtherfield Commons in Finsbury Park as a base for our photowalk! They were amazingly accommodating and we had a wonderful time chatting in general about art and what they were up to at the gallery and space.

They have some really neat things going on at the gallery and space so be sure to check them out if you can!

Going for a Walk with Friends

This is one of my favorite things about being able to attend LGM. I get to take a stroll and talk about photography with friends that I only usually get to interact with through an IRC window. I also feel like I can finally contribute something back to these awesome people that provide software I use every day.

We meandered through the park and chatted a bit about various things. Simon had brought along his external flash and wanted to play with off-camera lighting. So we convinced Liam to stand in front of a tree for us and Simon ended up taking one of my favorite images from the entire trip. This was Liam standing in front of the tree under the shade with me holding the flash slightly above him and to the camera right.

We even managed to run into Barrie Minney while on our way back to the Commons building. Aryeom and I started talking a little bit while walking when we crossed paths with some locals hanging out in the park. One man in particular was quite outgoing and let Aryeom take his photo, leading to another fun image!

Upon returning to the Commons building we experimented with some of the pretty window light coming into the building along with some black panels and a model (Mairi). This was quite fun as we were experimenting with various setups for the black panels and speedlights. Everyone had a chance to try some shots out and to direct Mairi (who was super patient and accommodating while we played).

Towards the end of our day I decided get my big Softlighter out and to try a few things in the lane outside the Commons building. Luckily Michael Schumacher grabbed an image of us while we were testing some shots with Mairi outside.

I loved the lane receding in the background and thought it might make for some fun images of Mairi. I had two YN-560 flashes in the Softlighter both firing around ¾ power. I had to balance the ambient sky with the softlighter so needed the extra power of a second flash (it also helps to keep the cycle times down).

The day was awesome and I really enjoyed being able to just hang out with everyone and take some neat photos. The evening at the pub was pretty great also (I got to hang out with Barrie and his friend and have a couple of pints - thanks again Barrie!).

LGM

It never fails to amaze me how every year the LGM organizers manage to put together such a great meeting for everyone. The venue was great and the people were just fantastic at the University of Westminster.

The opening “State of the Libre Graphics“ presentation was done by our (the GIMP teams) very own João Bueno who did a fantastic job! João will also be the local organizer for the 2017 LGM in Rio.

Thanks to contributions from community members Kees Guequierre, Jonas Wagner, and Philipp Haegi I had some great images to use for the PIXLS.US community slides for the “State of the Libre Graphics“. If anyone is curious, here is what I submitted:

These slides can be found on our Github PIXLS.US Presentations page (along with all of our other presentations that relate to PIXLS.US and promoting the community).

Speaking of presentations…

Presentation

I was given some time to talk about and present our community to everyone at the meeting. (See embedded slides below):

I started by looking at what my primary motivation was to begin the site and what the state of free software photography was like at that time (or not like). Mainly that the majority of resources online for photographers that were high quality (and focused on high-quality results) were usually aimed at proprietary software users. Worse still, in some cases these websites locked away their best tutorials and learning content behind paywalls and subscriptions. I finished by looking at what was done to build this site and forum as a community for everyone to learn and share with each other freely.

I think the presentation went well and people seemed to be interested in what we were doing! Nate Willis even published an article about the presentation at LWN.net, “Refactoring the open-source photography community”:

Exhibition

A nice change this year was the inclusion of an exhibition space to display works by LGM members and artists. We even got an opportunity to hang a couple of prints (for some reason they really wanted my quad-print of pippin). I was particularly happy that we were able to print and display the Green Tiger Beetle by community member Kees Guequierre:

Portraits

In Leipzig I thought it would be nice to offer portraits/headshots of folks that attended the meeting. I think it’s a great opportunity to get a (hopefully) nice photograph that people can use in social media, avatars, websites, etc. Here’s a sample of portraits from LGM2014 of the GIMP team that sat for me:

In 2014 I was lucky that houz had brought along an umbrella and stand to use, so this time I figured it was only fair that I bring along some gear myself. I had the Softlighter setup on the last couple of days for anyone that was interested in sitting for us. I say us because Marek Kubica (@Leonidas) from the community was right there to shoot with me along with the very famous @Ofnuts (well - famous to me - I’ve lost count of the neat things I’ve picked up from his advice)! Marek took quite a few portraits and managed the subjects very well - he was conversational, engaged, and managed to get some great personality from them.

A couple of samples from the images that I got are here as well, and they are the local organizer Lara with students from the University! I simply can’t thank them enough for the efforts and generosity in making us feel so welcome.

I’m still working through the portraits I took, but I’ll have them uploaded to my Flickr soon to share with everyone!

GIMPers

One of the best parts of attendance is getting to spend some time with the rest of the GIMP crew. Here’s an action shot during the GIMP meeting over lunch with a neat, glitchy schumaml:

It was great to see everyone at the flat on our last evening there as well…

Wrap up

Overall this was another incredible meeting bringing together great folks who are building and supporting Free Software and Libre Graphics. Just my kind of crowd!

I even got a chance to speak a bit with the wonderful Susan Spencer of the Valentina project and we roughed out some thoughts about getting together at some point. It turns out she lives just up the same state as me (Alabama)! This is simply too great to not take advantage of - Free Software Fashion + Photography?! That will have to be a fun story (and photos) for another day…

Keep watching the blog for some more images from the trip - up next are the portraits of everyone and some more shots of the venue and exhibition!

Sam Graydon looks at the poet Robert Browning, exploring the major role he played in the development of the dramatic monologue, with a selection of readings from his works.

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To mark the 400th anniversary of the death of Shakespeare and Cervantes, Mika Ross-Southall introduces a talk on these two giants of world literature.

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Michael Caines and Lucy Dallas take a tour of Thomas More's imaginary commonwealth, where private property has been abolished and reason rules all.

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Toby Lichtig talks to Morris Dickstein about the ever-evolving relationship between Judaism and American literature.

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Pre-LGM Photowalk

Time to take some photos!

It’s that time of year again! The weather is turning mild, the days are smelling fresh, and a bunch of photography nerds are all going to get together in a new country to roam around and (possibly) annoy locals by taking a ton of photographs! It’s the Pre-Libre Graphics Meeting photowalk of 2016!

Come join us the day before LGM kicks off to have a stroll through a lovely park and get a chance to shoot some photos between making new friends and having a pint.

Thanks to the wonderful work by the local LGM organizing team, we are able to invite everyone out to the photowalk on Thursday, April 14^th the day before LGM kicks off.

They were able to get us in touch with the kind folks at Furtherfield Gallery & Commons in Finsbury Park. They’ve graciously offered us the use of their facilities at the Furtherfield Commons as a base to start from. So we will meet at the Commons building at 10:00 on Thursday morning.

Pre-LGM Photowalk
10:00 (AM), Thursday, April 14^th
Furtherfield Commons
Finsbury Gate - Finsbury Park
Finsbury Park, London, N4 2NQ

An overview of the photowalk venue relative to the LGM venue at the University of Westminster, Harrow:

If you would like to join us but may not make it to the Commons by 10:00, email me and let me know. I’ll try my best to make arrangements to meet up so you can join us a little later. I can’t imagine we’d be very far away (likely somewhere relatively near by in the park).

We’ll plan on meandering through the park with frequent stops to shoot images that strike our fancy. I will personally be bringing along my off-camera lighting equipment and a model (Mairi) to pose for us during the day. In case anyone wanted to play/learn a little about that type of photography.

There is no set time for finishing up. I figured we would play it by ear through lunch and to possibly all finish up at a nice pub together. (Taking advantage of the golden hour light at the end of the day hopefully).

In the spirit of saying “Thank you!” and sharing, I have also offered the Furtherfield folks our services for headshots and architectural/environmental shots of the Commons and Gallery spaces. For sure I will be taking these images for them but if anyone else wanted to pitch in and try, help, or assist the effort would be very welcome!

Speaking of which, if you plan on attending and would like to explore some particular aspect of photography please feel free to let me know. I’ll do my best to match folks up based on interest. I sincerely hope this will be a fun opportunity to learn some neat new things, make some new friends, and to maybe grab some great images at the same time!

If there are any questions, please don’t hesitate to reach out to me!
`patdavid@gmail.com`
patdavid on irc://irc.gimp.org/#gimp

Happy Birthday DISCUSS.PIXLS.US

Where did the time go?!

For some reason I was checking my account on the forums earlier today and noticed that it was created in April, 2015. On further inspection it looks like my, and @darix, accounts were created on April 2^nd 2015.

(Not to be confused with the main site because apparently it took me about 8 months to get a forum stood up…)

Which means that the forums have been around for just over a year now?!

So, Happy Birthday discuss!

We’re just over a year old and just under 500 users on the forum!

For fun, I looked for the oldest (public) post we had and it looks like it’s the “Welcome to PIXLS.US Discussion“ thread. In case anyone wanted to revisit a classic…

THANK YOU so much to everyone who has made this an awesome place to be and nerd out about photography and software and more! Since we started we migrated the official G’MIC forums here as well as our friends at RawTherapee! We’ve been introduced to some awesome projects like PhotoFlow as well as Filmulator. And everyone has just been amazing, supportive, and fun to be around.

As I posted in the original Welcome thread…

Lighting Diagrams

Help Us Build Some Assets!

Community member Eric Mesa asked on the forums the other day if there might be some Free resources for photographers that want to build a lighting diagram of their work. These are the diagrams that show how a shot might be set up with the locations of lights, what types of modifiers might be used, and where the camera/photographer might be positioned with respect to the subject. These diagrams usually also include lighting power details and notes to help the production.

It turns out there wasn’t really anything openly available and permissively licensed. So we need to fix that…

These diagrams are particularly handy for planning a shoot conceptually or explaining what the lighting setup was to someone after the fact. For instance, here’s a look at the lighting setup for Sarah (Glance):

There are a few different commercial or restrictive-licensed options for photographers to create a lighting diagram, but nothing truly Free.

So thanks to the prodding by Eric, I thought it was something we should work on as a community!

I already had a couple of simple, basic shapes created in Inkscape for another tutorial so I figured I could at least get those files published for everyone to use.

I don’t have much to start with but that shouldn’t be a problem! I already had a backdrop, person, camera, octabox (+grid), and a softbox (+grid):

PIXLS.US Github Organization

I already have a GitHub organization setup just for PIXLS.US, you can find the lighting-diagram assets there:

https://github.com/pixlsus/pixls-lighting-diagram

Feel free to join the organization!

Even better: join the organization and fork the repo to add your own additions and to help us flesh out the available diagram assets for all to use! From the README.md on that repo, I compiled a list of things I thought might be helpful to create:

• Cameras
  • DSLR
  • Mirrorless
  • MF
• Strobes
  • Speedlight
  • Monoblock
• Lighting Modifiers
  • Softbox (+ grid?)
  • Umbrella (+ grid?)
  • Octabox (+ grid?)
  • Brolly
• Reflectors
• Flags
• Barn Doors / Gobo
• Light stands? (C-Stands?)
• Environmental
  • Chairs
  • Stools
  • Boxes
  • Backgrounds (+ stands)
• Models

If you don’t want to create something from scratch, perhaps grabbing the files and tweaking the existing assets to make them better in some way?

Hopefully we can fill out the list fairly quickly (as it’s a fairly limited subset of required shapes). Even better would be if someone picked up the momentum to possibly create a nice lighting diagram application of some sort!

The files that are there now are all licensed Creative Commons By-Attribution, Share-Alike 4.0.

PlayRaw (Again)

The Resurrectioning

On the old RawTherapee forums they used to have a contest sharing a single raw file amongst the members to see how everyone would approach processing from the same starting point. They called it PlayRaw. This seemed to really bring out some great work from the community so I thought it might be fun to start doing something similar again here.

I took a (relatively) recent image of Mairi and decided to see how it would be received (I’d say fairly well given the responses). This was my result from the raw file that I called Mairi Troisième:

I made the raw file available under a Creative Commons, By-Attribution, Non-Commercial, Share-Alike license so that anyone could freely download and process the file as they wanted to.

The only things I asked for was to see the results and possibly the processing steps through either an XMP or PP3 sidecar file (darktable and RawTherapee respectively).

Here’s a montage of the results from everyone:

I loved being able to see what everyone’s approaches looked like. It’s neat to get a feel for all the different visions out there among the users and there were some truly beautiful results!

If you haven’t given it a try yourself yet, head on over to the [PlayRaw] Mairi Troisieme thread to get the raw file and try it out yourself! Just don’t forget to show us your results in the topic.

I’ll be soliciting options for a new image to kick off another round of processing again soon.

Speaking of Mairi

Don’t forget that we still have a Pledgie Campaign going on to help us offset the costs of getting everyone together at the 2016 Libre Graphics Meeting in London this April!

Donations go to help cover to costs of various projects to come together and meet, photograph, discuss, and hack at things. Please consider donating as every little bit helps us immensely! If you can’t donate then please consider helping us to raise awareness of what we’re trying to do! Either link the Pledgie campaign to others or let them know we’re here to help and share!

Even better is if you’re in the vicinity of London this April 15–18! Come out and join us as well as many other awesome Free Software projects all focused on the graphics community! We (PIXLS) will be conducting photowalks and meet-ups the Thursday before LGM kicks off as well!

Oh, and I finally did convince Mairi to join us through the weekend to model for us as needed. She’s super awesome and worth raising a glass to/with! Even more reason to come out and join us!

Shimming an Adapter to be Parallel

Achieving perfect infinity focus

Some of you may know I exclusively use Contax manual focus lenses on my Canon cameras. I have had one reliable adapter from the start, that just happened to be perfect in every way: perfectly parallel, and lets my lenses focus exactly to infinity, and none of my lenses hit the mirror on my 5D.

However, swapping adapters between cameras gets mighty tedious, so recently I have been trying a variety of different adapters for my cameras, several quality tiers ranging from the cheapest ($15) up to the most expensive ($70).

However, I wasn’t satisfied with any of them. In order to assure that the adapted lenses can focus to infinity even with manufacturing tolerances, they’re made thinner than necessary. This means that they focus past infinity, and with some lenses the mirror of my 5D would hit the back of the lens, needing me to wiggle it to free the mirror after taking a photo.

I measured my fancier Fotodiox Pro adapter, and found that not only was it too thin, but it was unevenly thick! The top was 8 thousandths of an inch thin, the bottom right was 2 thousandth of an inch thin, and the bottom left was exactly the right thickness.

I decided I could do something about it.

I bought some shim stock from McMaster Carr, plastic and 2 thousandths of an inch thick, figuring I might be able to fold it to build up thickness if necessary. (Spoiler: it does fold.) It comes as a giant sheet five by twenty inches, but you’ll only need the tiniest amount of it.

Then I went about removing the screws that hold the two sides together.

The screws are incredibly small.

Here you can see that there are only three points on the ring that actually control the thickness; I point to one with the scissors. I had to be careful when measuring the thickness to only measure it between the screws, and that was challenging because the EF mount diameter is larger than the C/Y mount diameter, and there was only the slightest overlap between the outside of the C/Y registration surface and the inside of the EF mount.

Next I just cut a narrow strip out of this piece of shim stock using scissors, and put slits in it so it could fold more easily.

The right hand shim is folded in the shape of a W, and the left hand shim is only one layer.

The thicker shim went on the top, and the thinner shim went on the bottom-right.

Put the ring back on, and then…

Reinstall the screws.

Test your lenses for infinity focus and, if applicable, mirror slap, and rejoice if they’re good!

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If you don’t have a perfect adapter as a reference for the proper thickness, you can first adjust the adapter to be perfectly even thickness all the way around, and then you can add thickness uniformly until your lenses just barely focus to infinity. It might be time consuming, but it’s very rewarding being able to trust the infinity stop on your lenses.

This method isn’t only applicable to the two-part SLR->SLR Fotodiox adapters; it should also work for SLR or rangefinder to mirrorless adapters as well.

I’ve seen it written that you can’t be sure whether or not your adapters are even thickness all the way around, but with this technique, you can make sure that your adapters are perfect.

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Carlo originally posted this as a thread on the forums but I thought it would be useful as a post. He has graciously allowed us to re-publish it here. –Pat

Mika Ross-Southall and Michael Caines look at the enduring appeal of Thomas Chatterton, an icon of thwarted Romantic genius, and how he became a figure of especial importance for Oscar Wilde.

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To mark the centenary of Henry James's death, Catharine Morris and Michael Caines trace the course of his work as it was discussed in his lifetime – and as some of it appeared in the TLS itself.

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jpeg2RAW Guest Spot

An interview! LGM update! And Github?

Mike Howard, the host and creator of the jpeg2RAW podcast reached out to me last week to see if I might be able to come on the show to talk about Free Software Photography and what we’ve been up to here. One of the primary reasons for creating this site was to be able to raise awareness of the Free Software community to a wider audience.

So this is a great opportunity for us to expose ourselves!

Exposing Ourselves

The podcast airs live this Tuesday, February 23^rd at 8PM Eastern (-0500). You can join us at the jpeg2RAW live podcast page! Mike has the live feed available to watch on that page and also has a chat server set up so viewers can interact with us live during the broadcast.

If you are free on Tuesday night then come on by and join us! I’ll be happy to field any questions you want answered (and that Mike asks) and will do my best to not embarrass myself (or our community). If you would like to make sure I address something in particular (or just don’t forget something), I also have a thread on discuss where you can make sure I know it.

I’m also looking for community members to submit some photos to help highlight our work and what’s possible with Free Software. Feel free to link them in the same thread as above. I’ve already convinced andabata to point us to some of his great macro shots (like that awesome lede image) and I’ll be submitting a few of my own images as well. If you have some works that you’d like to share please let me know!

In Case You Miss It

Mike has all of his prior podcasts archived on his Podcasts page. So if you miss the live show it looks like you’ll be able to catch up later at your convenience.

LGM Update

As mentioned previously we are heading to London for Libre Graphics Meeting 2016! We’ve got a flat rented for a great crew to be able to stay together and we’re on track for a PIXLS meet up before LGM!

Speaking of people, I’m looking forward to being able to spend some time with some great folks again this year! We’ve got Tobias, Johannes, and Pascal making it out (I’m not sure that Simon, top below, will be making it out) from darktable, DrSlony and qogniw from RawTherapee, Andrea Ferrero creator of PhotoFlow, even Ofnuts (how cool is that?) may make it out!

We’ve also already had a great response so far on our Pledgie campaign. The campaign is still running if you want to help out!

If anyone is thinking they’d like to make it out to join us, please let me know as soon as possible so we can plan for space!

My friend and model Mairi will also be making it out for the meeting. She’ll be on hand to help us practice lighting setups, model interactions, and will likely be shooting right along with the rest of us as well!

I’ll also be assembling slides for my presentation during LGM. I’ve got a 20 minute time slot to talk about the community we’ve been building here and the neat things our members have been up to (Filmulator, PhotoFlow, and more).

Speaking of slides and sharing information…

Github Organization

I’ve setup a Github Pixls organization so that we can begin to share various things. This came about after talking with @paperdigits on the post about the upcoming podcast at jpeg2RAW. We were talking about ways to share information and assets for creating/delivering presentations about Free Software photography.

At the moment there is only the single repository Presentations as we are figuring out structure. I’ve uploaded my slides and notes from the LGM2015 State of the Libre Graphics presentation announcing PIXLS. If you’re on Github and want to join us just let me know!

On the 10th anniversary of her blog, A Don's Life, The TLS' Classics Editor Mary Beard joins Rozalind Dineen to discuss its success. Find out more: www.the-tls.co.uk

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HDR Photography with Free Software (LuminanceHDR)

A first approach to creating and mapping HDR images

I have a mostly love/hate relationship with HDR images (well, tonemapping HDR more than the HDR themselves). I think the problem is that it’s very easy to create really bad HDR images that the photographer thinks look really good. I know because I’ve been there:

The best term I’ve heard used to describe over-processed images created from an HDR is “clown vomit” (which would also be a great name for a band, by the way). They are easily spotted with some tell-tale signs such as the halos at high-contrast edges, the unrealistically hyper-saturated colors that make your eyes bleed, and a general affront to good taste. In fact, while I’m putting up embarrassing images that I’ve done in the past, here’s one that scores on all the points for a crappy image from an HDR:

Crap-tastic! Of course, the allure here is that it provides first timers a glimpse into something new, and they feel the desire to crank every setting up to 11 with no regards to good taste or aesthetics.

If you take anything away from this post, let it be this: “Turn it DOWN“. If it looks good to you, then it’s too much. ;)

HDR lightprobes are used in movie fx compositing to ensure that the lighting on CG models matches exactly the lighting for a live-action scene. By using an HDR lightprobe, you can match the lighting exactly to what is filmed.

I originally learned about, and used, HDR images when I would use them to illuminate a scene in Blender. In fact, I will still often use Paul Debevec’s Uffizi gallery lightprobe to light scene renders in Blender today.

For example, you may be able to record 10-12 stops of light information using a modern camera. Some old films could record 12-13 stops of light, while your eyes can approximately see up to 14 stops.

HDR images are intended to capture more than this number of stops. (Depending on your patience, significantly more in some cases).

I can go on a bit about the technical aspects of HDR imaging, but I won’t. It’s boring. Plus, I’m sure you can use Wikipedia, or Google yourselves. :) In the end, just realize that an HDR image is simply one where there is a greater amount of light information being stored than is able to be captured by your camera sensor in one shot.

Taking an HDR image(s)

More light information than my camera can record in one shot?
Then how do I take an HDR photo?

You don’t.

You take multiple photos of a scene, and combine them to create the final HDR image. Before I get into the process of capturing these photos to create an HDR with, consider something:

When/Why to use HDR

An HDR image is most useful to you when the scene you want to capture has bright and dark areas that fall outside the range of a single exposure, and you feel that there is something important enough outside that range to include in your final image.

That last part is important, because sometimes it’s OK to have some of your photo be too dark for details (or too light). This is an aesthetic decision of course, but keep it in mind…

Here’s what happens. Say you have a pretty scene you would like to photograph. Maybe it’s the Lower Chapel of Sainte Chapelle:

You may setup to take the shot, but when you are setting your exposure you may run into a problem. To expose for the brighter parts of the image means that the shadows fall to black too quickly, crushing out the details there.

If you expose for the shadows, then the brighter parts of the image quickly clip beyond white.

The use case for an HDR is when you can’t find a happy medium between those two exposures.

A similar situation comes up when you want to shoot any ground details against a bright sky, but you want to keep the details in both. Have a look at this example:

In the first column, if you expose for the ground, the sky blows out.

In the second, you can drop the exposure to bring the sky in a bit, but the ground is getting too dark.

In the third, the sky is exposed nicely, but the ground has gone to mostly black.

If you wanted to keep the details in the sky and ground at the same time, you might use an HDR (you could technically also use exposure blending with just a couple of exposures and blend them by hand, but I digress) to arrive at the last column.

Shooting Images for an HDR

Many cameras have an auto-bracketing feature that will let you quickly shoot a number of photos while changing the exposure value (EV) of each. You can also do this by hand simply by changing one parameter of your exposure each time.

You can technically change any of ISO, shutter speed, or aperture to modify the exposure, but I’d recommend you change only the shutter speed (or EV value when in Aperture Priority modes).

The reason is that changing the shutter speed will not alter the depth-of-field (DoF) of your view or introduce any extra noise the way changing the aperture or ISO would.

When considering your scene, you will also want to try to stick to static scenes if possible. The reason is that objects that move around (swaying trees, people, cars, fast moving clouds, etc.) could end up as ghosts or mis-alignments in your final image. So as you’re starting out, choose your scene to help you achieve success.

Set up your camera someplace very steady (like a tripod), dial in your exposure and take a shot. If you let your camera meter your scene for you then this is a good middle starting point.

For example, if you setup your camera and meter your scene, it might report a ¹⁄₁₆₀ second exposure. This is our starting point (0EV).

To capture the lower values, just cut your shutter speed in half ( ¹⁄₈₀ second, +1EV), and take a photo. Repeat if you’d like ( ¹⁄₄₀ second, +2EV).

To capture the upper values, just double your starting point shutter speed ( ¹⁄₃₂₀, -1EV) and take a photo. Repeat if you’d like again ( ¹⁄₆₄₀, -2EV).

This will give you 5 images covering a range of -2EV to +2EV:

Shutter Speed	Exposure Value
1⁄640	-2EV
1⁄320	-1EV
1⁄160	0EV
1⁄80	+1EV
1⁄40	+2EV

Your values don’t have to be exactly 1EV each time, LuminanceHDR is usually smart enough to figure out what’s going on from the EXIF data in your image - I chose full EV stops here to simplify the example.

So armed with your images, it’s time to turn them into an HDR image!

Creating an HDR Image

You kids have it too easy these days. We used to have to bring all the images into Hugin and align them before we could save an hdr/exr file. Nowadays you’ve got a phenomenal piece of Free/Open Source Software to handle this for you:

LuminanceHDR
(Previously qtpfsgui. Seriously.)

After installing it, open it up and hit “New HDR Image“:

This will open up the “HDR Creation Wizard” that will walk you through the steps of creating the HDR. The splash screen notes a couple of constraints.

On the next screen, you’ll be able to load up all of the images in your stack. Just hit the big green “+“ button in the middle, and choose all of your images:

LuminanceHDR will load up each of your files, and investigate them to try and determine the EV values for each one. It usually does a good job of this on its own, but if there a problem you can always manually specify what the actual EV value is for each image.

Also notice that because I only adjusted my shutter speed by half or double, that each of the relative EV values is neatly spaced 1EV apart. They don’t have to be, though. I could have just as easily done ½ EV or ⅓ EV steps as well.

If there is even the remotest question about how well your images will line up, I’d recommend that you check the box for “Autoalign images”, and let Hugin’s align_image_stack do it’s magic. You really need all of your images to line up perfectly for the best results.

Hit “Next“, and if you are aligning the images be patient. Hugin’s align_image_stack will find control points between the images and remap them so they are all aligned. When it’s done you’ll be presented with some editing tools to tweak the final result before the HDR is created.

You are basically looking at a difference view between images in your stack at the moment. You can choose which two images to difference compare by choosing them in the list on the left. You can now shift an image horizontally/vertically if it’s needed, or even generate a ghosting mask (a mask to handle portions of an image where objects may have shifted between frames).

If you are careful, and there’s not much movement in your image stacks, then you can safely click through this screen. Hit the “Next“ button.

This is the final screen of the HDR Creation Wizard. There are a few different ways to calculate the pixel values that make up an HDR image, and this is where you can choose which ones to use. For the most part, people far smarter than I had a look at a bunch of creation methods, and created the predefined profiles. Unless you know what you’re doing, I would stick with those.

Hit “Finish“, and you’re all done!

You’ll now be presented with your HDR image in LuminanceHDR, ready to be tonemapped so us mere mortals can actually make sense of the HDR values present in the image. At this point, I would hit the “Save As…” button, and save your work.

Tonemapping the HDR

So now you’ve got an HDR image. Congratulations!

The problem is, you can’t really view it with your puny little monitor.

The reason is that the HDRi now contains more information than can be represented within the limited range of your monitor (and eyeballs, likely). So we need to find a way to represent all of that extra light-goodness so that we can actually view it on our monitors. This is where tonemapping comes in.

We basically have to take our HDRi and use a method for compressing all of that radiance data down into something we can view on our monitors/prints/eyeballs. We need to create a Low Dynamic Range (LDR) image from our HDR.

Yes - we just went through all the trouble of stacking together a bunch of LDR images to create the HDRi, and now we’re going back to LDR ? We are - but this time we are armed with way more radiance data than we had to begin with!

The question is, how do we represent all that extra data in an LDR? Well, there’s quite a few different ways. LuminanceHDR provides for 9 different tonemapping operators (TMO’s) to represent your HDRi as an LDR image:

• Mantiuk ‘06
• Mantiuk ‘08
• Fattal
• Drago
• Durand
• Reinhard ‘02
• Reinhard ‘05
• Ashikhmin
• Pattanaik

Just a small reminder, there’s a ton of math involved in how to map these values to an LDR image. I’m going to skip the math. The references are out there if you want them.

I’ll try to give examples of each of the operators below, and a little comment here and there. If you want more information, you can always check out the list on the Open Source Photography wikidot page.

Before we get started, let’s have a look at the window we’ll be working in:

Tonemap is the section where you can choose which TMO you want to use, and will expose the various parameters you can change for each TMO. This is the section you will likely be spending most of your time, tweaking the settings for whichever TMO you decide to play with.

Process gives you two things you’ll want to adjust. The first is the size of the output that you want to create (Result Size). While you are trying things out and dialing in settings you’ll probably want to use a smaller size here (some operators will take a while to run against the full resolution image). The second is any pre-gamma you want to apply to the image. I’ll talk about this setting a bit later on.

Oh, and this section also has the “Tonemap” button to apply your settings and generate a preview. I’ll also usually keep the “Update current LDR” checked while I rough in parameters. When I’m fine-tuning I may uncheck this (it will create a new image every time you hit the “Tonemap” button).

Results are shown in this big center section of the window. The result will be whatever Result Size you set in the previous section.

Previews are automatically generated and shown in this column for each of the TMO. If you click on one, it will automatically apply that TMO to your image and display it (at a reduced resolution - I think the default is 400px, but you can change it if you want). It’s a nice way to quickly get a preview overview of what all the different TMOs are doing to your image.

Ok, with that out of the way, let’s dive into the TMOs and have a look at what we can do. I’m going to try to aim for a reasonably realistic output here that (hopefully) won’t make your eyeballs bleed. No promises, though.

Need an HDR to follow along? I figured it might be more fun (easier?) to follow along if you had the same file I do.
So here it is, don’t say I never gave you anything (This hdr is licensed cc-by-sa-nc by me):
Download from Google Drive (41MB .hdr)

Another note - all of the operators can have their results tweaked by modification of the pre-gamma value ahead of time. This is applied the image before the TMO is applied, and will make a difference in the final output. Usually pushing the pre-gamma value down will increase contrast/brightness in the image, while increasing it will do the opposite. I find it better to start with pre-gamma set to 1 as I experiment, just remember that it is another factor that you use to modify your final result.

Mantiuk ‘06

I’m starting with this one because it’s the first in the list of TMOs. Let’s see what the defaults from this operator look like against our base HDRi:

By default Mantiuk ‘06 produces a muted color result that seems pleasing to my eye. Overall the image feels like it’s almost “dirty” or “gritty” with these results. The default settings produce a bit of extra local contrast boosting as well.

Let’s see what the parameters do to our image.

Contrast Factor

The default factor is 0.10.

Pushing this value down to as low as 0.01 produces just a slight increase in contrast across the image from the default. Not that much overall.

Pushing this value up, though, will tone down the contrast overall. I think this helps to add some moderation to the image, as hard contrasts can be jarring to the eyes sometimes. Here is the image with only the Contrast Factor pushed up to 0.40:

Saturation Factor

The default value is 0.80.

This factor just scales the saturation in the image, and behaves as expected. If you find the colors a bit muted using this TMO, you can bump this value a bit (don’t get crazy). For example, here is the Saturation Factor bumped to 1.10:

Of course, you can also go the other way if you want to mute the colors a bit more:

Detail Factor

The default is 1.0.

The Detail Factor appears to control local contrast intensity. It gets overpowering very quickly, so make small movements here (if at all). Here is what pushing the Detail Factor up to 10.0 produces:

Contrast Equalization

This is supposed to equalize the contrast if there are heavy swings of light/dark across the image on a global scale, but in my example did little to the image (other than a strange lightening in the upper left corner).

My Final Version

I played a bit starting from the defaults. First I wanted to push down the contrast a bit to make everything just a bit more realistic, so I pushed Contrast Factor up to 0.30. I slightly bumped the Saturation Factor to 0.95 as well.

I liked the textures of the tree and house, so I wanted to bring those back up a bit after decreasing the Contrast Factor, so I pushed the Detail Factor up to 5.0.

Here is what I ended up with in the end:

Mantiuk ‘08

Mantiuk ‘08 is a global contrast TMO (for comparison, Mantiuk ‘06 uses local contrast heavily). Being a global operator, it’s very quick to apply.

As you can see, the effect of this TMO is to compress the dynamic range into an LDR output using a function that operates across the entire image globally. This will produce a more realistic result I think, overall.

The default output is not bad at all, where brights seem appropriately bright, and darks are dark while still retaining details. It does feel like the resulting output is a little over-sharp to my eye, however.

There are only a couple of parameters for this TMO (unless you specifically override the Luminance Level with the checkbox, Mantiuk ‘08 will automatically adjust it for you):

Predefined Display

There are options for LCD Office, LCD, LCD Bright, and CRT but they didn’t seem to make any difference in my final output at all.

Color Saturation

The default is 1.0.

Color Saturation operates exactly how you’d expect. Dropping this value decreases the saturation, and vice versa. Here’s a version with the Color Saturation bumped to 1.50:

Contrast Enhancement

The default value is 1.0.

This will affect the global contrast across the image. The default seemed to have a bit too much contrast, so it’s worth it to dial this value in. For instance, here is the Contrast Enhancement dialed down to 0.51:

Compared to the default settings I feel like this operator can work better if the contrast is turned down just a bit to make it all a little less harsh.

Enable Luminance Level

This checkbox/slider allows you to manually specify the Luminance Level in the image. The problem that I ran into was that with this enabled, I couldn’t adjust the Luminance far enough to keep bright areas in the image from blowing out. if I let the default behavior of automatically adjusting Luminanace, then it kept things more under control.

My Final Version

Starting from the defaults, I pushed down the Contrast Enhancement to 0.61 to even out the overall contrast. I bumped the Color Saturation to 1.10 to bring out the colors a bit more as well.

I also dropped the pre-gamma correction to 0.91 in order to bring back some of the contrast lost from the Contrast Enhancement.

Fattal

Crap. Time for this TMO I guess…

THIS is the TMO responsible for some of the greatest sins of HDR images. Did you see the first two images in this post? Those were Fattal. The problem is that it’s really easy to get stupid with this TMO.

Fattal (like the other local contrast operators) is dependent on the final output size of the image. When testing this operator, do it at the full resolution you will want to export. The results will not match up if you change size. I’m also going to focus on using only the newer v.2.3.0 version, not the old one.

Here is what the default values look like on our image:

The defaults are pretty contrasty, and the color seems saturated quite a bit as well. Maybe we can get something useful out of this operator. Let’s have a look at the parameters.

Alpha

The default is 1.00.

This parameter is supposed to be a threshold against which to apply the effect. According to the wikidot, decreasing this value should increase the level of details in the output and vice versa. Here is an example with the Alpha turned down to 0.25:

Increasing the Alpha value seems to darken the image a bit as well.

Beta

The default value is 0.90.

This parameter is supposed to control the amount of the algorithm applied on the image. A value of 1 is no effect on the image (straight gamma=1 mapping). Lower values will increase the amount of the effect. Recommended values are between 0.8 and 0.9. As the values get lower, the image gets more cartoonish looking.

Here is an example with Beta dropped down to 0.75:

Color Saturation

The default value is 1.0.

This parameter does exactly what’s described. Nothing interesting to see here.

Noise Reduction

The default value is 0.

This should suppress fine detail noise from being picked up by the algorithm for enhancement. I’ve noticed that it will slightly affect the image brightness as well. Fine details may be lost if this value is too high. Here the Noise Reduction has been turned up to 0.15:

My Final Version

This TMO is sensitive to changes in its parameters. Small changes can swing the results far, so proceed lightly.

I increased the Noise Reduction a little bit up front, which lightened up the image. Then I dropped the Beta value to let the algorithm work to brighten up the image even further. To offset the increase, I pushed Alpha up a bit to keep the local contrasts from getting too harsh. A few minutes of adjustments yielded this:

Overall, Fattal can be easily abused. Don’t abuse the Fattal TMO. If you find your values sliding too far outside of the norm, step away from your computer, get a coffee, take a walk, then come back and see if it still hurts your eyes.

Drago

Drago is another of the global TMOs. It also has just one control: bias.

Here is what the default values produce:

The default values produced a very washed out appearance to the image. The black points are heavily lifted, resulting in a muddy gray in dark areas.

Bias is the only parameter for this operator. The default value is 0.85. Decreasing this value will lighten the image significantly, while increasing it will darken it. For my image, even pushing the Bias value all the way up to 1.0 only produced marginal results:

Even at this level the image still appears very washed out. The only other parameter to change would be the pre-gamma before the TMO can operate. After adjusting values for a bit, I settled on a pre-gamma of 0.67 in addition to the Bias being set to 1:

My Final Version

Durand

Most of the older documentation/posts that I can find describe Durand as the most realistic of the TMOs, yielding good results that do not appear overly processed.

Indeed the default settings immediately look reasonably natural, though it does exhibit a bit of blowing out in very bright areas - which I imagine can be fixed by adjustment of the correct parameters. Here is the default Durand output:

There are three parameters that can be adjusted for this TMO, let’s have a look:

Base Contrast

The default is 5.00.

This value is considered a little high from most sources I’ve read. Usually recommending to drop this value to the 3-4 range. Here is the image with the Base Contrast dropped to 3.0:

The Base Contrast does appear to drop the contrast in the image, but it also drops the blown-out high values on the house to more reasonable levels.

Spatial Kernel Sigma

The default value is 2.00.

This parameter seems to produce a change to contrast in the image. Large value swings are required to notice some changes, depending on the other parameter values. Pushing the value up to 65.00 looks like this:

Range Kernel Sigma

The default value is 2.00.

My limited testing shows that this parameters doesn’t quite operate correctly. Changes will not modify the output image until you reach a certain threshold in the upper bounds, where it will overexpose the image. I am assuming there is a bug in the implementation, but will have to test further before filing a bug report.

My Final Version

In experiment I found that pre-gamma adjustments can affect the saturation in the output image. Pushing pre-gamma down a bit will increase the saturation.

I pulled the Base Contrast back to keep the sides of the house from blowing out. Once I had done that, I also dropped the pre-gamma to 0.88 to bump the saturation slightly in the colors. A slight boost to Spatial Kernel Sigma let me increase local contrasts slightly as well.

Finally, I used the Adjust Levels dialog to modify the levels slightly by raising the black point a small amount (hey - I’m the one writing about all these #@$%ing operators, I deserve a chance to cheat a little).

Reinhard ‘02

This is supposed to be another very natural looking operator. The initial default result looks good with medium-low contrast and nothing blowing out immediately:

Even though many parameters are listed, they don’t really appear to make a difference. At least with my test HDR. Even worse, attempting to use the “Use Scales” option usually just crashes my LuminanceHDR.

Key Value

The default is 0.18.

This appears to be the only operator that does anything in my image at the moment. Increasing it will increase the brightness of the image, and decreasing it will darken the image.

Here is the image with Key Value turned down to 0.05:

Phi

The default is 1.00.

This parameter does not appear to have any affect on my image.

Use Scales

Turning this option on currently crashes my session in LuminanceHDR.

My Final Version

I started by setting the Key Value very low (0.01), and adjusted it up slowly until I got the highlights about where I wanted them. Due to this being the only parameter that modified the image, I then started adjusting pre-gamma up until I got to roughly the exposure I thought looked best (1.09).

Reinhard ‘05

Reinhard ‘05 is supposed to be another more ‘natural’ looking TMO, and also operates globally on the image. The default settings produce an image that looks under-exposed and very saturated:

There are three parameters for this TMO that can be adjusted.

Brightness

The default value is -10.00.

Interestingly, pushing this parameter down (all the way to its lowest setting, -20) did not darken my image at all. Pulling it up, however, did increase the brightness overall. Here the brightness is increased to -2.00:

Chromatic Adaptation

The default is 0.00.

This parameter appears to affect the saturation in the image. Increasing it desaturates the results, which is fine given that the default value of 0.00 shows a fairly saturated image to begin with. Here is the Chromatic Adaptation turned up to 0.60:

Light Adaptation

The default is 1.00.

This parameter modifies the global contrast in the final output. It starts at the maximum of 1.00, and decreasing this value will increase the contrast in the image. Pushing the value down to 0.5 does this to the test image:

My Final Version

Starting from the defaults, I raised the Brightness to -5.00 to lift the darker areas of the image, while keeping an eye on the highlights to keep them from blowing out. I then decreased the Light Adaptation until the scene had a reasonable amount of contrast without becoming overpowering to 0.75. At that point I turned up the Chromatic Adaptation to reduce the saturation in the image to be more realistic, and finished at 0.60.

Ashikhmin

This TMO has little in the way of controls - just options for two different equations that can be used, and a slider. The default (Eqn. 2) image is very dark and heavily saturated:

There is a checkbox option for using a “Simple” method (that produces identical results regardless of which Eqn is checked - I’m thinking it doesn’t use that information).

Simple

Checking the Simple checkbox removes any control over the image parameters, and yields this image:

Fairly saturated, but exposed reasonably well. It lacks some contrast, but the tones are all there. This result could use some further massaging to knock down the saturation and to bump the contrast slightly (or adjust pre-gamma).

Equation 4

This is the result of choosing Equation 4 instead:

There is a large loss of local contrast details in the scene, and some of the edges appear very soft. Overall the exposure remains very similar.

Local Contrast Threshold

The default value is 0.50.

This parameter modifies the local contrast being applied to the image. The result will be different depending on which Equation is being used.

Here is Equation 2 with the Local Contrast Threshold reduced to 0.20:

Lower values will decrease the amount of local contrast in the final output.

Equation 4 with Local Contrast Threshold reduced to 0.20:

My Final Version

After playing with the options, the overall best version I feel is had by just using the Simple option. Further tweaking may be necessary to get usable results beyond this.

Pattanaik

This TMO appears to attempt to mimic the behavior of human eyes with the inclusion of terminology like “Rod” and “Cone”. There are quite a few different parameters to adjust if wanted. The default TMO results in an image like this:

The default results are very desaturated, and tends to blow out in the highlights. The dark areas appear well exposed, with the problems (in my test hdr) being mostly constrained to highlights for this example. On first glance, the results look like something that could be worked with.

There are quite a few different parameters for this TMO. Let’s have a look at them:

Multiplier

The default value is 1.00.

This parameter appears to modify the overall contrast in the image. Decreasing the value will decrease contrast, and vice versa. It also appears to slightly modify the brightness in the image as well (pushing the highlights to a less blown-out value). Here is the Multiplier decreased to 0.03:

Local Tone Mapping

This parameter is just a checkbox, with no controls. The result is a washed out image with heavy local contrast adjustments:

Cone/Rod Levels

The default is to have Auto Cone/Rod checked, greying out the options to change the parameters manually.

Turning off Auto Cone/Rod will get the default manual values of 0.50 for both applied:

The image gets very blown out everywhere, and modification of the Cone/Rod values does not significantly reduce brightness across the image.

My Final Version

Starting with the defaults, I reduced the Multiplier to bring the highlights under control. This reduced contrast and saturation in the image.

To bring back contrast and some saturation, I decreased the pre-gamma to 0.91. The results are not too far off of the defualt settings. The results could still use some further help with global contrast and saturation, and might benefit from layering or modifications in GIMP.

Closing Thoughts

Looking through all of the results shows just how different each TMO will operate across the same image. Here are all of the final results in a single image:

I personally like the results from Mantiuk ‘06. The problem is that it’s still a little more extreme than I would care for in a final result. For a really good, realistic result that I think can be massaged into a great image, I would go to Mantiuk ‘08 or Reinhard.

I could also do something with Fattal, but would have to tone a few things down a bit.

While you’re working, remember to occasionally open up the Levels Adjustment to keep an eye on the histogram. Look for highlights blowing out, and shadows becoming too murky. All the normal rules of image processing still apply here - so use them!

You’re trying to use HDR as a tool for you to capture more information, but remember to still keep it looking realistic. If you’re new to HDR processing, then I can’t recommend enough to stop occasionally, get away from the monitor, and come back to look at your progress.

If it hurts your eyes, dial it all back. Heck, if you think it looks good, still dial it back .

If I can head off even one clown-vomit image, then I’ll consider my mission accomplished with this post.

A Couple of Further Resources

Here’s a few things I’ve found scattered around the internet if you want to read more.

• The Open Source Photography wikidot page has some information as well
• Cambridge in Colour user David has written about many of the operators:
  • Mantiuk
  • Fattal
  • Drago
  • Durand
  • Reinhard 05
  • Reinhard 02
  • Ashikhmin
  • Pattanaik
• A little Finnish exploration of global vs. local operators

We also have a sub-category on the forums dedicated entirely to LuminanceHDR and HDR processing in general: https://discuss.pixls.us/c/software/luminancehdr.

This tutorial was originally published here.

Michael Caines and Catharine Morris celebrate the bicentenary of Jane Austen's magnificent novel and its quixotic heroine.Find out more: www.the-tls.co.uk

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