Users Guide to High Bit Depth GIMP 2.9.2, Part 1

Part 1: New high bit depth precision options, new color space algorithms, and new color management options

Contents

1. Introduction: high bit depth GIMP 2.9.2
   1. Purpose of this guide
   2. Useful links: the official GIMP website, builds for Windows and MAC, building GIMP on Linux
   3. Editing in sRGB vs editing in other color spaces
   4. A note about the “Gamma hack” that’s provided for many editing operations
2. New high bit depth precision options
   1. Menu for choosing the image precision
   2. Which precision should you choose for editing?
   3. Using the image precision options when exporting an image to disk
3. New color management options
   1. GIMP 2.9.2 automatically detects camera DCF information
   2. Black point compensation
4. New and updated algorithms for converting to Luminance, LAB, and LCH
   1. Converting sRGB images from Color to Black and White using Luma and Luminance
   2. Decomposing from sRGB to LAB
   3. LCH: the actually usable replacement for the entirely inadequate color space known as “HSV”

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Introduction: high bit depth GIMP 2.9.2

Purpose of this guide

As announced on the GIMP users and developers mailing lists, the recent (November 26, 2015) GIMP 2.9.2 release is the first development release in the GIMP 2.9.x series leading to GIMP 2.10. The release announcement summarizes the many code changes that were made to port the old GIMP code over to GEGL’s high bit depth processing.

This user’s guide to high bit depth GIMP 2.9.2 introduces you to some of high bit depth GIMP’s new editing capabilities that are made possible by GEGL’s high bit depth processing. The guide also points out a few “gotchas” that you should be aware of. Please keep in mind that GIMP 2.9 really is a development branch, so many things don’t yet work exactly like they will work when GIMP 2.10 is released.

Useful links: the official GIMP website, builds for Windows and MAC, building GIMP on Linux

• GIMP website
• GIMP IRC and mailing list information
• Partha’s GIMP 2.9 builds for Windows and MAC, including a portable Windows build of my patched GIMP plus information on compiling GIMP on Windows.
• Precompiled versions of high bit depth GIMP are more or less widely available for the various Linux operating systems. If you run Linux and you’d like to compile high bit depth GIMP yourself, Building GIMP for artists and photographers has step-by-step instructions.

High bit depth GIMP is a work in progress. If you read the release notes for GIMP 2.9.2, you already know that the primary goal for the GIMP 2.10 release is full “Geglification” of the GIMP code base.

Editing in sRGB vs editing in other color spaces

For best results when using GIMP 2.9.2, only edit sRGB images.

GIMP 2.8 has hard-coded sRGB parameters that make many editing operations produce wrong results for images that are in RGB working spaces other than sRGB. GIMP 2.9.2 still has these hard-coded sRGB parameters. Almost certainly GIMP 2.10 also will have these same hard-coded sRGB parameters.

Full support for editing images in other RGB working spaces won’t happen at least until GIMP 3.0, and maybe not until some time after GIMP 3.0. The next big change for GIMP will be the change-over from GTK+2 to GTK+3, which is a pretty critical step to make as GTK+2 is on the verge of being retired. GIMP development is a volunteer effort, porting GIMP over to GEGL has required an enormous amount of work, and porting from GTK+2 to GTK+3 isn’t exactly a trivial task. More GIMP developers would help a lot, so if you have any coding skills, please consider volunteering.

If you really do want to edit in color spaces other than sRGB “right now”, and you are comfortable building GIMP from git, my patched version of GIMP 2.9 is hard-coded to use the much larger Rec.2020 color space, and it should be obvious how to modify the patches for other RGB working spaces.

A note about the “Gamma hack” that’s provided for many editing operations

A “Gamma hack” option is provided by many GIMP 2.9.2 editing operations. This option sits next to some text that says “(temp hack, please ignore)”. Unless you know exactly what you are doing, you really are better off not using the Gamma hack.

New high bit depth precision options

Menu for choosing the image precision

As shown by the screenshot below, GIMP 2.9.2 offers six different image precisions:

• Three integer precisions: 8-bit integer, 16-bit integer, and 32-bit integer.
• Three floating point precisions: 16-bit floating point, 32-bit floating point, and 64-bit floating point.

Which precision should you choose for editing?

If you have a fast computer with a lot of RAM, I recommend that you always promote your images to 32-bit floating point before you begin editing. Here’s why:

1. Regardless of which precision you choose, all babl/GEGL/GIMP internal processing is done at 32-bit floating point. Read that sentence three times.
2. There seems to be a small speed penalty for not using 32-bit floating point precision.
3. The Precision menu options dictate how much memory is used to store in RAM the results of internal calculations:
   • Choosing 32-bit floating point precision allows you to take full advantage of GEGL’s 32-bit floating point processing.
   • If you are working on a lower-RAM machine, performance will benefit from using 16-bit floating point or integer precision, but of course the price is a loss in precision as new editing operations use the results of previous edits as stored in memory.
   • On very low RAM systems, performance will benefit even more from using 8-bit integer precision. But if you use 8-bit integer precision, you are throwing away most of the advantages of working with a high bit depth image editor.
   • 64-bit precision is made available mostly to accommodate importing and exporting very high bit precision images for scientific editing. You don’t gain any computational precision from using 64-bit precision for actual editing. If you choose 64-bit precision for editing, all you are really doing is wasting system RAM resources.

As discussed in Part 2 of this article, “Using GIMP 2.9.2’s floating point precision for unclamped editing” (and depending on your editing style and goals), instead of 32-bit floating point precision, sometimes you might prefer using 16-bit or 32-bit integer precision. But making full use of all of high bit depth GIMP’s new editing capabilities does require using floating point precision.

Using the image precision options when exporting an image to disk

The precision menu options have another extremely important use beside dictating the precision with which the results of editing operations are held in RAM. When you export the image to disk, the precision options allow you to change the bit depth of the exported image.

For example, some image editors can’t read floating point tiffs. So if you want to export an image as a tiff file that will be opened in another image editor that can only read 8-bit and 16-bit integer tiffs, and your GIMP XCF layer stack is currently using 32-bit floating point precision, you might want to change the XCF layer stack precision to 16-bit integer before exporting the tiff.

After exporting the image, don’t forget to hit “UNDO” (“Edit/Undo . . . “, or else just use the CNTL-Z keyboard shortcut) to get back to 32-bit floating point precision (or whatever other precision you were using).

New color management options

GIMP 2.9.2 automatically detects camera DCF information

For reasons only the camera manufacturers know, instead of embedding a proper ICC profile in camera-saved jpegs, usually they embed “DCF” and “maker note” information. Whenever a camera manufacturer offers the option to embed a color space that isn’t officially supported by the DCF/Exif standards, each manufacturer feels free to improvise with new tags.

GIMP 2.9.2 does detect and assign the correct color space for most camera-saved jpegs. Like all editing software, GIMP has to play “catch up” with new tags for new color spaces offered by new camera models.

Tell your camera manufacturer that you want proper ICC profiles embedded in your camera-saved jpegs.

Black point compensation

Unlike GIMP 2.8, GIMP 2.9 does offer black point compensation as an explicit option, and it’s enabled by default.

Even though black point compensation is checked by default in GIMP 2.9.2, whether you should use black point compensation partly depends on the color management settings provided by the other imaging software that you routinely use. For example, Firefox doesn’t provide for black point compensation. As far as I can tell, neither does RawTherapee or darktable. If one of your goals is to make sure that images look the same as displayed in various softwares, you need to make sure all the relevant color management settings match.

What is black point compensation? LCD monitors can’t display “zero light”. There’s always some minimum amount of light coming from the screen. Fill your screen with a solid black image, turn out all the lights and close the doors and curtains, and you’ll see what I mean.

Black point compensation compensates for the fact that RGB working spaces like sRGB allow you to produce colors (for example solid black) that are darker than your monitor can actually display. GIMP uses the LCMS black point compensation algorithm, which very sensibly scales the image tonality so that “solid black” in the image file maps to “darkest dark” in the monitor profile’s color gamut.

However, depending on your monitor profile, using or not using black point compensation might not make any difference at all. The only time black point compensation makes a difference is if the Monitor profile you choose in “Preferences/Color management” actually does have a “higher than zero” black point.

Why some monitor profiles do and some don’t have “higher than zero” black points is beyond the scope of this tutorial. Suffice it to say that a very accurate LCD monitor profile will always have a higher than zero black point. But sometimes, and especially for consumer-grade monitors, a very accurate monitor profile will make displayed images look worse than they will when using a less accurate monitor profile.

New and updated algorithms for converting to Luminance, LAB, and LCH

Converting sRGB images from Color to Black and White using Luma and Luminance

Under “Colors/Desaturate”, GIMP 2.8 offers three options for converting an sRGB image to black and white: Lightness, Luminosity, and Average:

1. The “Lightness” option adds the lowest and highest RGB channel values and divides the result by two.
2. The “Luminosity” option is equal to (the Red channel times 0.213) plus (the Green channel times 0.715) plus (the Blue channel times 0.072).
3. The “Average” option sums all three RGB channel values and divides the result by three.

GIMP 2.9.2 still offers all three options for converting an sRGB image to black and white. But the “Luminosity” option has been renamed Luma, which is the technically correct term (though various image editors use the term “Luminosity” in various incorrect ways.

Also GIMP 2.9.2’s “Luma” option uses slightly different multipliers for calculating Luma, being (the Red channel times 0.222) plus (the Green channel times 0.717) plus (the Blue channel times 0.061). The GIMP 2.8 multipliers were wrong and the GIMP 2.9 multipliers are correct.

Since I know you won’t be able to get any sleep until someone tells you why the multipliers for calculating Luma were changed, the GIMP 2.9 multipliers have been Bradford-adapted from D65 to D50, which is required for use in an ICC profile color-managed editing application (at least until the next version of the ICC specs is released and people figure out how to deal with the new freedom to use non-D50 reference white points).

GIMP 2.9.2 also offers a fourth option for converting sRGB images to black and white, which is “Luminance”. “Luminance” is short for relative luminance. Luminance is calculated using the same channel multipliers that are used to calculate Luma. The mathematical difference between calculating Luma and Luminance is as follows:

• Luma is calculated using RGB channel values that are encoded using the sRGB TRC.
• Luminance is calculated using linearized RGB channel values, producing a radiometrically correct and physically meaningful conversion from color to black and white.

Of the various options in the “Colors/Desaturate” menu, “Luminance” is the only physically meaningful way to convert from color to black and white.

The Red, Blue, and Green Luma and Luminance channel multipliers are specific to the sRGB color space. These channel multipliers are actually the “Y” components of the sRGB ICC profile’s XYZ primaries. As you might expect, different RGB working spaces have different “Y” values, and so the GIMP 2.9.2 conversions to Luma and Luminance only produce correct results for sRGB images.

Decomposing from sRGB to LAB

Decomposing to LAB does use hard-coded sRGB parameters and so will produce wrong results in other RGB working spaces.

In GIMP 2.8, decomposing an sRGB image to LAB produced flatly wrong results. In GIMP 2.9.2, decomposing an sRGB image to LAB does produce mathematically correct results. But if you use “drag and drop” to pull the decomposed grayscale layers over to your sRGB layer stack, there is still a small error in the resulting RGB layer. Figure 3 below illustrates the problem:

Assuming you start with an image in the regular sRGB color space, then:

• In GIMP 2.9.2, decomposing a layer to LAB in GIMP 2.9 produces mathematically correct results.

  However, dragging the resulting grayscale channels back to the RGB XCF color stack results in a slightly wrong result. This is because the dropped grayscale layer(s), which don’t have an embedded ICC profile, are assumed to be encoded using the sRGB companding curve (Tone Reproduction Curve, “TRC”), when really they are encoded using the LAB companding curve. This is a color management problem that can be solved by enabling GIMP to do grayscale color management (all that’s needed is a little developer time — did I mention that GIMP really does need more developers?).

  As an incredibly important aside, a mathematically correct conversion from sRGB to LAB Lightness and back to sRGB produces exactly the same thing as using GIMP 2.9.2’s “Colors/Desaturate/Luminance” option to change an sRGB image from color to black and white.

• In GIMP 2.8, decomposing a layer to LAB produces wildly mathematically incorrect results, and dragging the resulting channel(s) back to the RGB XCF color stack also produces wildly mathematically incorrect results. So older GIMP tutorials on using the LAB Lightness channel to convert an image to black and white won’t produce anywhere near the same results when using GIMP 2.9/GIMP 2.10.

If you’d like to know more about “LAB Lightness to black and white”, the following two-part article untangles the massive amounts of confusion regarding converting an RGB image to black and white using the LAB Lightness channel:

1. LAB Lightness to black and white using GIMP 2.8.
2. LAB Lightness to black and white using GIMP 2.9 and PhotoShop (the typical PhotoShop tutorial on using the LAB Lightness channel to convert to black and white does produce mathematically incorrect results).

LCH: the actually usable replacement for the entirely inadequate color space known as “HSV”

LCH calculations do use hard-coded sRGB parameters, and so will produce wrong results in other RGB working spaces.

HSV (“Hue/Saturation/Value”) is a sad little color space designed for fast processing on slow computers, way back in the stone age of digital processing. HSV is OK for picking colors from a color wheel. But it’s really wretched for just about any other editing application, because despite the fact that “HSV” stands for “Hue/Saturation/Value”, you actually can’t adjust color and tonality separately in the HSV color space.

“LCH” stands for “Lightness, Chroma, Hue”. LCH is mathematically derived from the CIELAB reference color space, which in turn is a perceptually uniform transform of the CIEXYZ reference color space. Unlike HSV, LCH is a physically meaningful color space that allows you to edit separately for color and tonality.

Very roughly speaking:

• LCH Lightness corresponds to HSV Value.
• LCH Chroma corresponds to HSV Saturation.
• LCH Hue corresponds to HSV Hue (the names are the same, but the two blend modes are based on very different mathematics).
• LCH Color is a combination of LCH Chroma and Hue, and corresponds to HSV Color, which is a combination of HSV Hue and Saturation (again, the names are the same, but the two blend modes are based on very different mathematics).

LCH blend modes and painting are a game-changing addition to high bit depth GIMP editing capabilities. If you’d like to see examples of what you can do with LCH, that you can’t even come close to doing with HSV, I’ve written a couple of tutorials on using GIMP’s LCH color space capabilities:

1. A tutorial on GIMP’s very awesome LCH Blend Modes, which shows how to use GIMP’s new LCH blend modes to repair a badly damaged image, and then to colorize a black and white rendering of the image.
2. Autumn colors: An Introduction to High Bit Depth GIMP’s New Editing Capabilities, which shows how to use GIMP’s new LCH blend modes to edit separately for color and tonality.

I’m not an especially skilled programmer. In fact I find writing code to be a painfully slow exercise. But one major reason why I maintain a patched version of high bit depth GIMP is precisely so I can use the LCH color space not just for blending and painting, but also for picking colors and as a replacement for the essentially useless HSV “Hue-Saturation” tool. These particular editing capabilities will eventually make it into an official GIMP release, but I didn’t want to wait for “eventually” to happen.

Click here to go to Part 2 of this guide to GIMP 2.9.2!
Part 2 discusses using GIMP 2.9.2 to do radiometrically correct editing, unbounded ICC profile conversions, and unclamped editing.

All text and images ©2015 Elle Stone, all rights reserved.

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Michael Caines looks back to Douglas Oliver's long poem The Infant and the Pearl, first published in 1985 – a poetic vision of the contemporary political scene, among other things, cast in the mould of a medieval dream poem.Find out more: www.the-tls.com

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Portrait Lighting Cheat Sheets

Blender to the Rescue!

Many moons ago I had written about acquiring a YN-560 speedlight for playing around with off-camera lighting. At the time I wanted to experiment with how different modifiers might be used in a portrait setting. Unfortunately, these were lighting modifiers that I didn’t own yet.

I wasn’t going to let that slow me down, though!

If you want to skip the how and why to get straight to the cheat sheets, click here.

Infinite Realities had released a full 3D scan by Lee Perry-Smith of his head that was graciously licensed under a Creative Commons Attribution 3.0 Unported License. For reference, here is a link to the object file and textures (80MB) and the displacement maps (65MB) from the Infinite Realities website.

What I did was to bring the high resolution scan and displacement maps into Blender and manually created my lights with modifiers in a virtual space. Then I could simply render what a particular light/modifier would look like with a realistic person being lit in any way I wanted.

This leads to all sorts of neat freedom to experiment with things to see how they might come out. Here’s another look at the lede image:

I had originally intended to make a nice bundled application that would allow someone to try all sorts of different lighting setups, but my skill in Blender only go so far. My skills at convincing others to help me didn’t go very far either. :)

So, if you’re ok with navigating around Blender already, feel free to check out my original blog post to download the .blend file and give it try! Jimmy Gunawan even took it further and modified the .blend to work with Blender cycles rendering as well.

With the power to create a lighting visualization of any scenario I then had to see if there was something cool I could make for others to use…

The Lighting Cheat Sheets

I couldn’t help but generate some lighting cheat sheets to help others use as a reference. I’ve seen some different ones around but I took advantage of having the most patient model in the world to do this with. :)

These were generated by rotating a 20” (virtual) softbox in a circle around the subject at 3 different elevations (0, 30°, and 60°).

Click the caption title for a link to the full resolution files:

Hopefully these might prove useful as a reference for some folks. Share them, print them out, tape them to your lighting setups! :) I wonder if we could get some cool folks from the community to make something neat with them?

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We discuss a poem by J.H. Prynne called To Pollen, from 2006, which conducts its own examination of the uses and misuses of images and stories of suffering.Read by Robert Potts.Find out more: www.the-tls.co.uk

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Softness and Superresolution

Experimenting and Clarifying

A small update on how things are progressing (hint: well!) and some neat things the community is playing with.

I have been quiet these past few weeks because I decided I didn’t have enough to do and thought a rebuild/redesign of the GIMP website would be fun, apparently. Well, it _is_ fun and something that couldn’t hurt to do. So I stepped up to help out.

A Question of Softness

There was a thread recently on a certain large social network in a group dedicated to off-camera flash. The thread was started by someone with the comment:

The most important thing you can do with your speed light is to put some rib [sic] stop sail cloth over the speed light to soften the light.

Which just about gave me an aneurysm (those that know me and lighting can probably understand why). Despite some sound explanations about why this won’t work to “soften” the light, there was a bit of back and forth about it. To make matters worse, even after over 100 comments, nobody bothered to just go out and shoot some sample images to see it for themselves.

So I finally went out and shot some to illustrate and I figured they would be more fun if they were shared (I did actually post these on our forum).

I quickly set a lightstand up with a YN560 on it pointed at my garden statue. I then took a shot with bare flash, one with diffusion material pulled over the flash head, and one with a 20” diy softbox attached.

Here’s what the setup looked like with the softbox in place:

Remember, this was done to demonstrate that simply placing some diffusion fabric over the head of a speedlight does nothing to “soften” the resulting light:

This shows clearly that diffusion material over the flash head does nothing to affect the “softness” of the resulting light.

For a comparison, here is the same shot with the softbox being used:

I also created some crops to help illustrate the difference up close:

Hopefully this demonstration can help put to rest any notion of softening a light through close-set diffusion material (at not-close flash-to-subject distances). At the end of the day, the “softness” quality of a light is a function of the apparent size of the light source relative to the subject. (The sun is the biggest light source I know of, but it’s so far it’s quality is quite harsh.)

A Question of Scaling

On discuss, member Mica asked an awesome question about what our workflows are for adding resolution (upsizing) to an image. There were a bunch of great suggestions from the community.

One I wanted to talk about briefly I thought was interesting from a technical perspective.

Both Hasselblad and Olympus announced not too long ago the ability to drastically increase the resolution of images in their cameras that used a “sensor-shift” technology to shift the sensor by a pixel or so while shooting multiple frames, then combing the results into a much larger megapixel image (200MP in the case of Hasselblad, and 40MP in the Olympus).

It turns out we can do the same thing manually by burst shooting a series of images while handholding the camera (the subtle movement of our hand while shooting provides the requisite “shift” to the sensor). Then we simply combine the images, upscale, and average the results to get a higher resolution result.

The basic workflow uses Hugin align_image_stack, Imagemagick mogrify, and G’MIC mean blend script to achieve the results.

1. Shoot a bunch of handheld images in burst mode (if available).
2. Develop raw files if that’s what you shot.
3. Scale images up to 4x resolution (200% in width and height). Straight nearest-neighbor type of upscale is fine.
   • In your directory of images, create a new sub-directory called resized.
   • In your directory of images, run mogrify -scale 200% -format tif -path ./resized *.jpg if you use jpg’s, otherwise change as needed. This will create a directory full of upscaled images.
4. Align the images using Hugin’s align_image_stack script.
   • In the resized directory, run /path/to/align_image_stack -a OUT file1.tif file2.tif ... fileX.tif The -a OUT option will prefix all your new images with OUT.
   • I move all of the OUT* files to a new sub-directory called aligned.
5. In the aligned directory, you now only need to mean average all of the images together.
   • Using Imagemagick: convert OUTfile*.tif -evaluate-sequence mean output.bmp
   • Using G’MIC: gmic video-avg.gmic -avg \" *.tif \" -o output.bmp

I used 7 burst capture images from an iPhone 6+ (default resolution 3264x2448). This is the test image:

Here is a 100% crop of the first area:

The second area crop:

Obviously this doesn’t replace the ability to have that many raw pixels available in a single exposure, but if the subject is relatively static this method can do quite well to help increase the resolution. As with any mean/median blending technique, a nice side-effect of the process is great noise reduction as well…

Not sure if this warrants a full article post, but may consider it for later.

Freaky Details (Calvin Hollywood)

Replicating Calvin Hollywood's Freaky Details in GIMP

German photographer/digital artist/photoshop trainer Calvin Hollywood has a rather unique style to his photography. It’s a sort of edgy, gritty, hyper-realistic result, almost a blend between illustration and photography.

As part of one of his courses, he talks about a technique for accentuating details in an image that he calls “Freaky Details”.

Here is Calvin describing this technique using Photoshop:

In my meandering around different retouching tutorials I came across it a while ago, and wanted to replicate the results in GIMP if possible. There were a couple of problems that I ran into for replicating the exact same workflow:

1. Lack of a “Vivid Light” layer blend mode in GIMP
2. Lack of a “Surface Blur” in GIMP

Those problems have been rectified (and I have more patience these days to figure out what exactly was going on), so let’s see what it takes to replicate this effect in GIMP!

Replicating Freaky Details

Requirements

The only extra thing you’ll need to be able to replicate this effect is G’MIC for GIMP.

You don’t technically need G’MIC to make this work, but the process of manually creating a Vivid Light layer is tedious and error-prone in GIMP right now. Also, you won’t have access to G’MIC’s Bilateral Blur for smoothing. And, seriously, it’s G’MIC - you should have it anyway for all the other cool stuff it does!

Summary of Steps

Here’s the summary of steps we are about to walk through to create this effect in GIMP:

1. Duplicate the background layer.
2. Invert the colors of the top layer.
3. Apply “Surface Blur” to top layer.
4. Set top layer blend mode to “Vivid Light”.
5. New layer from visible.
6. Set layer blend mode of new layer to “Overlay”, hide intermediate layer.

There are just a couple of small things to point out though, so keep reading to be aware of them!

Detailed Steps

I’m going to walk through each step to make sure it’s clear, but first we need an image to work with!

As usual, I’m off to Flickr Creative Commons to search for a CC licensed image to illustrate this with. I found an awesome portrait taken by the U.S. National Guard/Staff Sergeant Christopher Muncy:

This is a great image to test the effect, and to hopefully bring out the details and gritty-ness of the portrait.

1./2. Duplicate background layer, and invert colors

So, duplicate your base image layer (Background in my example).

Layer → Duplicate
(Shift-Ctrl-D,Shift-⌘-D)

I will usually name the duplicate layer something descriptive, like “Temp” ;).

Next we’ll just invert the colors on this “Temp” layer.

Colors → Invert

So right now, we should be looking at this on our canvas:

Now that we’ve got our inverted “Temp” layer, we just need to apply a little blur.

3. Apply “Surface Blur” to Temp Layer

There’s a couple of different ways you could approach this. Calvin Hollywood’s tutorial explicitly calls for a Photoshop Surface Blur. I think part of the reason to use a Surface Blur vs. Gaussian Blur is to cut down on any halos that will occur along edges of high contrast.

There are three main methods of blurring this layer that you could use:

1. Straight Gaussian Blur (easiest/fastest, but may halo - worst results)

   Filters → Blur → Gaussian Blur

2. Selective Gaussian Blur (closer to true “Surface Blur”)

   Filters → Blur → Selective Gaussian Blur

3. G’MIC’s Smooth [bilateral] (closest to true “Surface Blur”)

   Filters → G’MIC → Repair → Smooth [bilateral]

I’ll leave it as an exercise for the reader to try some different methods and choose one they like. (At this point I personally pretty much just always use G’MIC’s Smooth [bilateral] - this produces the best results by far).

For the Gaussian Blurs, I’ve had good luck with radius values around 20% - 30% of an image dimension. As the blur radius increases, you’ll be acting more on larger local contrasts (as opposed to smaller details) and run the risk of halos. So just keep an eye on that.

So, let’s try applying some G’MIC Bilateral Smoothing to the “Temp” layer and see how it looks!

Run the command:

Filters → G’MIC → Repair → Smooth [bilateral]

The values you want to fiddle with are the Spatial Variance and Value Variance (25 and 20 respectively in my example). You can see the values I tried for this walkthrough, but I encourage you to experiment a bit on your own as well!

Now we should see our canvas look like this:

Now we just need to blend the “Temp” layer with the base background layer using a “Vivid Light” blending mode…

4./5. Set Temp Layer Blend Mode to Vivid Light & New Layer

Now we need to blend the “Temp” layer with the Background layer using a “Vivid Light” blending mode. Lucky for me, I’m friendly with the G’MIC devs, so I asked nicely, and David Tschumperlé added this blend mode for me.

So, again we start up G’MIC:

Filters → G’MIC → Layers → Blend [standard] - Mode: Vivid Light

Pay careful attention to the Input/Output portion of the dialog. You’ll want to set the Input Layers to All visibles so it picks up the Temp and Background layers. You’ll also probably want to set the Output to New layer(s).

When it’s done, you’re going to be staring at a very strange looking layer, for sure:

Now all that’s left is to hide the “Temp” layer, and set the new Vivid Light result layer to Overlay layer blending mode…

6. Set Vivid Light Result to Overlay, Hide Temp Layer

We’re just about done. Go ahead and hide the “Temp” layer from view (we won’t need it anymore - you could delete it as well if you wanted to).

Finally, set the G’MIC Vivid Light layer output to Overlay layer blend mode:

The results we should be seeing will have enhanced details and contrasts, and should look like this (mouseover to compare the original image):

This technique will emphasize any noise in an image so there may be some masking and selective application required for a good final effect.

Summary

This is not an effect for everyone. I can’t stress that enough. It’s also not an effect for every image. But if you find an image it works well on, I think it can really do some interesting things. It can definitely bring out a very dramatic, gritty effect (it works well with nice hard rim lighting and textures).

The original image used for this article is another great example of one that works well with this technique:

I had muted the colors in this image before applying some Portra-esque color curves to the final result..

Finally, a BIG THANK YOU to David Tschumperlé for taking the time to add a Vivid Light blend mode in G’MIC.

Try the method out and let me know what you think or how it works out for you! And as always, if you found this useful in any way, please share it, pin it, like it, or whatever you kids do these days…

This tutorial was originally published here.

Addendum

For those looking for a faster/easier way to achieve this effect, it has now been integrated as a filter into G’MIC. (Again, thanks to David Tschumperlé!)

Notes from the dark(table) Side

A review of the Open Source Photography Course

We recently posted about the Open Source Photography Course from photographer Riley Brandt. We now also have a review of the course as well.

This review is actually by one of the darktable developers, houz! He had originally posted it on discuss as a topic but I think it deserves a blog post instead. (When a developer from a favorite project speaks up, it’s usually worth listening…)

Here is houz’s review:

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The Open Source Photography Course Review

by houz

It seems that there is no topic to discuss The Open Source Photography Course yet so let’s get started.

Disclaimer

First of all, as a darktable developer I am biased so take everything I write with a grain of salt. Second, I didn’t pay for my copy of the videos but Riley was kind enough to provide a free copy for me to review. So add another pinch of salt. I will therefore not tell you if I would encourage you to buy the course. You can have my impressions nevertheless.

Review

I won’t say anything about the GIMP part, not because it wouldn’t know how to use that software but it’s relatively short and I just didn’t notice anything to comment on. It’s solid basics of how to use GIMP and the emphasis on layer masks is really important in real world usage.

Now for the darktable part, I have to say that I liked it a lot. It showcases a viable workflow and is relatively complete – not by explaining every module and becoming the audio book of the user manual but by showing at least one tool for every task. And as we all know, in darktable there are many ways to skin a cat, so concentrating on your favourites is a good thing.

What I also appreciate is that Riley managed to cut the single topics to manageable chunks of around 10 minutes or less so you can easily watch them in your lunch break and have no problem to come back to one topic later and easily find what you are looking for.

Before this starts to sound like an advertisement I will just point out some small nitpicking things I noticed while watching the videos. Most of these were not errors in the videos but are just extra bits of information that might make your workflow even smoother, so it’s more of an addendum than an erratum.

• When going through your images on lighttable you can either zoom in till you only see a single image (alt-1 is a shortcut for that) or hold the z key pressed. Both are shown in the videos. The latter can quickly become tedious since releasing z just once bring you back to where you were. There are however two more keyboard shortcuts that are not assigned by default under views>lighttable: ‘sticky preview’ and ‘sticky preview with focus detection’. Both work just like normal z and ctrl-z, just without the need to keep the key pressed. You can assign a key to these, for example by reusing z and ctrl-z.
• Color labels can be set with F1 .. F5, similar to rating.
• Basecurve and tonecurve allow very fine up/down movement of points with the mouse wheel. Hover over a node and scroll.
• Gaussian in shadows&highlights tends to give stronger halos than bilateral in normal use, see the darktable blog for an example.
• For profiled denoising better use ‘HSV color’ instead of ‘color’ and ‘HSV lightness’ instead of ‘lightness’, see the user manual for details.
• When using the mouse wheel to zoom the image you can hold ctrl to get it smaller than fitting to the screen. That’s handy to draw masks over the image border.
• When moving the triangles in color zones apart you actually widen the scope of affected values since the curve gets moved off the center line on a wider range.
• Also color zones: You can also change reds and greens in the same instance, no need for multiple instances. Riley knows that and used two instances to be able to control the two changes separately.
• When loading sidecar files from lighttable, you can even treat a JPEG that was exported from darktable like an XMP file and manually select that since the JPEGs get the processing data embedded. It’s like a backup of the XMP with a preview. Caveat: When using LOTS of mask nodes (mostly with the brush mask) the XMP data might get too big so it’s no longer possible to embed in the JPEG, but in general it works.
• The collect module allows to store presets so you can quickly access often used search rules. And since presets only store the module settings and not the resulting image set these will be updated when new images are imported.
• In neutral density you can draw a line with the right mouse button, similar to rotating images.
• Styles can also be created from darkroom, there is a small button next to the history compression button.

So, that’s it from me. Did you watch the videos, too? What was your impression? Do you have any remarks?

“August for the people and their favourite islands”, said W.H. Auden in 1935, with the Isle of Wight in mind. Now people’s favourite islands are more likely to be Majorca or Mykonos, but the lure of the seaside remains. Alan Jenkins reads a selection of holiday poems from the past eighty years.Find out more: www.the-tls.co.uk

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Color Curves Matching

Sample points and matching tones

In my previous post on Color Curves for Toning/Grading, I looked at the basics of what the Curves dialog lets you do in GIMP. I had been meaning to revisit the subject with a little more restraint (the color curve in that post was a little rough and gross, but it was for illustration so I hope it served its purpose).

This time I want to look at the use of curves a little more carefully. You’d be amazed at the subtlety that gentle curves can produce in toning your images. Even small changes in your curves can have quite the impact on your final result. For instance, have a look at the four film emulation curves created by Petteri Sulonen (if you haven’t read his page yet on creating these curves, it’s well worth your time):

I can’t thank Petteri enough for releasing these curves for everyone to use (for us GIMP users, there is a .zip file at the bottom of his post that contains these curves packaged up). Personally I am a huge fan of the Portraesque curve that he has created. If there is a person in my images, it’s usually my go-to curve as a starting point. It really does generate some wonderful skin tones overall.

The problem in generating these curves is that one has to be very, very familiar with the characteristics of the film stocks you are trying to emulate. I never shot Velvia personally, so it is hard for me to have a reference point to start from when attempting to emulate this type of film.

What we can do, however, is to use our personal vision or sense of aesthetic to begin toning our images to something that we like. GIMP has some great tools for helping us to become more aware of color and the effects of each channel on our final image. That is what we are going to explore…

Disclaimer I cannot stress enough that what we are approaching here is an entirely subjective interpretation of what is pleasing to our own eyes. Color is a very complex subject and deserves study to really understand. Hopefully some of the things I talk about here will help pique your interest to push further and experiment!
There is no right or wrong, but rather what you find pleasing to your own eye.

Approximating Tones

What we will be doing is using Sample Points and the Curves dialog to modify the color curves in my image above to emulate something else. It could be another photograph, or even a painting.

I’ll be focusing on the skin tones, but the method can certainly be used for other things as well.

With an image you have, begin considering what you might like to approximate the tones on. For instance, in my image above I want to work on the skin tones to see where it leads me.

Now find an image that you like, and would like to approximate the tones from. It helps if the image you are targeting already has tones somewhat similar to what you are starting with (for instance, I would look for another Caucasian image with similar tones to start from, as opposed to Asian). Keeping tones at least similar will reduce the violence you’ll do to your final image.

So for my first example, perhaps I would like to use the knowledge that the Old Masters already had in regards to color, and would like to emulate the skin tones from Vermeer’s Girl with the Pearl Earring.

In GIMP I will have my original image already opened, and will then open my target image as a new layer. I’ll pull this layer to one side of my image to give me a view of the areas I am interested in (faces and skin).

I will be using Sample Points extensively as I proceed. Read up on them if you haven’t used them before. They are basically a means of giving you real-time feedback of the values of a pixel in your image (you can track up to four points at one time).

I will put a first sample point somewhere on the higher skin tones of my base image. In this case, I will put one on my models forehead (we’ll be moving it around shortly, so somewhere in the neighborhood is fine).

Ctrl + Left Click in the ruler area of your main window (shown in green above), and drag out into your image. There should be crosshairs across your entire image screen showing you where you are dragging.

When you release the mouse button, you’ve dropped a Sample Point onto your image. You can see it in my image above as a small crosshair with the number 1 next to it.

GIMP should open the sample points dialog for you when you create the first point, but if not you can access it from the image menu under:

Windows → Dockable Dialogs → Sample Points

This is what the dialog looks like. You can see the RGB pixel data for the first sample point that I have already placed. As you place more sample points, they will each be reflecting their data on this dialog.

You can go ahead and place more sample points on your image now. I’ll place another sample point, but this time I will put it on my target image where the tones seem similar in brightness.

What I’ll then do is change the data being shown in the Sample Points dialog to show HSV data instead of Pixel data.

Now, I will shoot for around 85% value on my source image, and try to find a similar value level in similar tones from my target image as well. Once you’ve placed a sample point, you can continue to move it around and see what types of values it gives you. (If you use another tool in the meantime, and can no longer move just the sample point - you can just select the Color Picker Tool to be able to move them again).

Move the points around your skin tones until you get about the same Value for both points.

Once you have them, make sure your original image layer is active, then start up the curves dialog.

Colors → Curves…

Now here is something really handy to know while using the Curves dialog: if you hover your mouse over your image, you’ll notice that the cursor is a dropper - you can click and drag on an area of your image, and the corresponding value will show up in your curves dialog for that pixel (or averaged area of pixels if you turn that on).

So click and drag to about the same pixel you chose in your original image for the sample point.

Here is what my working area currently looks like:

I have my curves dialog open, and an area around my sample point chosen so that the values will be visible in the dialog, my images with their associated sample points, and the sample points dialog showing me the values of those points.

The basic idea now is to adjust my RGB channels to get my original image sample point (#1) to match my target image sample point (#2).

Because I selected an area around my sample point with the curves dialog open, I will know roughly where those values need to be adjusted. Let’s start with the Red channel.

First, set the Sample Points dialog back to Pixel to see the RGBA data for that pixel.

We can now see that to match the pixel colors we will need to make some adjustments to each channel. Specifically,

the Red channel will have to come down a bit (218 → 216),

the Green down some as well (188 → 178),

and Blue much more (171 → 155).

You may want to resize your Curves dialog window larger to be able to more finely control the curves. If we look at the Red channel in my example, we would want to adjust the curve down slightly at the vertical line that shows us where our pixel values are:

We can adjust the red channel curve along this vertical axis (marked x:217) until our pixel red value matches the target (216).

Then just change over to the green channel and do the same:

Here we are adjusting the green curve vertically along the axis marked x:190 until our pixel green value matches the target (178).

Finally, follow the same procedure for the blue channel:

As before, we adjust along the vertical axis x:173 until our blue channel matches the target (155).

At this point, our first sample point pixel should be the same color as from our target.

The important thing to take away from this exercise is to be watching your image as you are adjusting these channels to see what types of effects they produce. Dropping the green channel should have seen a slight addition of magenta to your image, and dropping the blue channel should have shown you the addition of a yellow to balance it.

Watch your image as you make these changes.

Don’t hit OK on your curves dialog yet!

You’ll want to repeat this procedure, but using some sample points that are darker than the previous ones. Our first sample points had values of about 85%, so now let’s see if we can match pixels down below 50% as well.

Without closing your curves dialog, you should be able to click and drag your sample points around still. So I would set your Sample Points dialog to show you HSV values again, and now drag your first point around on your image until you find some skin that’s in a darker value, maybe around 40-45%.

Once you do, try to find a corresponding value in your target image (or something close at least).

I managed to find skin tones with values around 45% in both of my images:

In these darker tones, I can see that the adjustments I will have to make are for:

Red down a bit (116 → 114),

Green bumped up some (60 → 73),

Blue slightly down (55 → 53).

With the curves dialog still active, I then click and drag on my original image until I am in the same area as my sample point again. This give me my vertical line showing me the value location in my curves dialog, just as before:

At this point you should have something similar to the tones of your target image. Here is my image after these adjustments so far:

Once you’ve got things in a state that you like, it would be a good idea to save your progress. At the top of the Curves dialog there is a “+” symbol. This will let you add the current settings to your favorites. This will allow you to recall these settings later to continue working on them.

However, you’re results might not quite look right at the moment. So why not?

Well, the first problem is that Sample Points will only allow you to sample a single pixel value. There’s a chance that the pixels you pick are not truly representative of the correct skin tones in that range (for instance you may have inadvertently clicked a pixel that represents the oil paint cracks in the image). It would be nice if there were an option for Sample Points to allow an adjustable sample radius (if there is an option I haven’t found it yet).

The second issue is that similar value points might be very different colors overall. Hopefully your sources will be nice for you to pick in areas that you know are relatively consistent and representative of the tones you want, but it’s not always a guarantee.

If the results are not quite what you want at the moment, you can do what I will sometimes do and go back to the beginning…

While still keeping the curves dialog open you can pull your sample points to another location, and match the target again. Try choosing another sample point with a similar value as the first one. This time instead of adding new points the curve as you make adjustments, just drag the existing points you previously placed.

It’s an Iterative Process

Depending on how interested you are in tweaking your resulting curve, you may find yourself going around a couple of times. That’s ok.

I would recommend keeping your curves to having two control points at first. You want your curves to be smooth across the range (any abrupt changes will do strange things to your final image).

If you are doing a couple of iterations, try modifying existing points on your curves instead of adding new ones. It may not be an exact match, but it doesn’t have to be. It only needs to look nice to your eyes.

There won’t be a perfect solution for a perfect color matching between images, but we can produce pleasing curves that emulate the results we are looking for.

In Conclusion

I personally have found the process of doing this with different images to be quite instructive in how the curves will affect my image. If you try this out and pay careful attention to what is happening while you do it, I’m hopeful you will come away with a similar appreciation of what these curves will do.

Most importantly, don’t be constrained by what you are targeting, but rather use it as a stepping off point for inspiration and experimentation for your own expression!

I’ll finish with a couple of other examples…

And finally, as promised, here’s the video tutorial that steps through everything I’ve explained above:

From a request, I’ve packaged up some of the curves from this tutorial (Pearl Earring, St. Michael, the previous Orange/Teal Hell, and another I was playing with from a Norman Rockwell painting): Download the Curves (7zip .7z)

New Discuss Categories and Logging In

Software, Showcase, and Critiques. Oh My!

Hot on the heels of our last post about welcoming G’MIC to the forums at discuss.pixls.us, I thought I should speak briefly about some other additions I’ve recently made.

These were tough for me to finally make a decision about. I want to be careful and not get crazy with over-categorization. At the same time, I do want to make good logical breakdowns for people that is still intuitive.

Here is what the current category breakdown looks like for discuss:

• PIXLS.US
  The comment/posts from articles/blogposts here on the main site.
• Processing
  Processing and managing images after they’ve been captured.
• Capturing
  Capturing an image and the ways we go about doing it.
• Showcase
• Critique
• Meta
  Discussions related to the website or the forum itself.
  • Help!
    Help with the website or forums.
• Software
  Discussions about various software in general.
  • G’MIC
    Topics all about G’MIC.

Along with the addition of the Software category (and the G’MIC subcategory), I decided that the Help! category would make more sense under the Meta category. That is, the Help! section is for website/forum help, which is more of a Meta topic (hence moving it).

Software

As we’ve already seen, there is now a Software category for all discussions about the various software we use. The first sub-category to this is of course, the G’MIC subcategory.

If there is enough interest in it, I am open to creating more sub-categories as needed to support particular software projects (GIMP, darktable, RawTherapee, etc…). I will wait until there is some interest before adding more categories here.

Showcase

This category had some interest from members and I agree that it’s a good idea. It’s intended as a place for members to showcase the works they’re proud of and to hopefully serve as a nice example of what we’re capable of producing using F/OSS tools.

A couple of examples from the Showcase category so far:

There may be a use of this category later for storing submissions for a rotating lede image on the main page of the site.

Critique

This is intended as a place for members to solicit advice and critiques on their works from others. It took me a little work to come up with an initial take on the overall description for the category.

I can promise that I will do my best to give honest and constructive feedback to anyone that asks in this category. I also promise to do my best to make sure that no post goes un-answered here (I know how beneficial feedback has been to me in the past, so it’s the least I could do to help others out in return).

Discuss Login Options

I also bit the bullet this week and finally caved to sign up for a Facebook account. The only reason was because I had to have a personal account to get an API key to allow people to log in using their FB account (with OAuth).

On the other hand, we now accept four different methods of logging in automatically along with signing up for a normal account. I have been trying to make it as frictionless as possible to join the conversation and hopefully this most recent addition (FB) will help in some small way.

Oh, and if you want to add me on Facebook, my profile can be found here. I also took the time to create a page for the site here: PIXLS.US on Facebook.