6

I have recently come across several pictures that seem to have been modified to favour or skew towards both yellow and blue tones. The photo editing effect creates a special, somewhat cosy ambiance.

Here is a nice example, with more examples at the [source]: Gary, N3GO, operating 80m straight through the night without leaving the oh-so-comfortable lawn chair

This other portrait [source] —with eyes too blue to be true— also seems to be affected.

My questions:

  • What is the name for this yellow-blue photo editing effect?
  • How can I recreate this effect with GIMP?

My own answer

To get the full zist and most detailed reverse-engineered solution, check out my own answer by clicking the image below.

reverse engineered image

  • Looking at the background on the final photo, I expect lighting was a factor on it. I don't know the GIMP equivalent, but in Photoshop an adjustment layer using levels could provide a blue/yellow tint. – Crazy Dino Nov 10 '16 at 15:20
  • The eyes in the last picture were almost certainly enhanced significantly on top of the effect you're looking for. – Chris H Nov 10 '16 at 16:12
  • 1
    I don't have a suitable image here to test and publish but from a quick play: Start with an image that already has some blue/yellow contrast (tungsten lamp and monitor, sodium streetlights and halogen or LED lights, gels on portrait lighting). Decompose to RGB. Decrease contrast on B channel, increase on the other 2. Recompose. You may still need to play with contrast and white balance – Chris H Nov 10 '16 at 16:21
  • 1
    My previous comment doesn't work too well. You can stretch it a little but too much and you end up with a sort of early 80s film effect. I've answered with a different method. – Chris H Nov 11 '16 at 13:53
3

I agree with the earlier answers that the example photos primarily got that way by use of lighting rather than post-processing; and I don't have a name for an effect that enhances yellow-blue contrast, but I do have a suggestion for how to achieve the effect in the GIMP.

The key tool is a colourspace called L*a*b*. If you open your image, go to Colors | Components | Decompose, and decompose to LAB, you'll get an image with layers called L, A, and B, or three images whose titles include L, A, and B.

L is the brightness. A is the red-green channel: red is 255, green is 0. B is the yellow-blue channel: yellow is 255, blue is 0. So by using tools such as Curves and Levels from the Colors menu separately on the A and B layers you can desaturate the red-green channel and saturate the yellow-blue channel. Taken to absolute extremes (threshold B, flatten A to a uniform medium grey) on Chris H's demo image, the result is

seriously oversaturated yellow-blue

With a smooth curve on B mapping 96 to 64 and 160 to 192, and another on A mapping 0 to 64 and 255 to 192, the result is a still overdone but not so badly:

less oversaturated yellow-blue

You can really notice the difference on the off-white table and wall, on the raspberry, and on the blue (copper sulphate, I'm guessing) liquid.

7

All of the example photos could have been made without any selective processing with regard to color temperature/white balance. They all look like they were made with several different types of light sources in the scene. If one light source is very orange and the other is very blue, the camera will see the difference much more so than our own eye/brain systems will.

In any of the below images were the color temperature and white balance set at a point in between the two light sources (rather to make one or the other look "white") the warmer one would look yellow/orange and the cooler one would look blue. If the color saturation were increased the differences would be even more notable.

Here's a photo I took at a football stadium in which the lights illuminating the field were much bluer than the lights illuminating the concourse area behind the stands. The only editing adjustments made were global which affected all parts of the picture equally.

When corrected for the very limited spectrum orange vapor lights (well beneath 2000K which necessitated use of the color picker) under the stands the light on the field looks very blue.

enter image description here

Yet when properly balancing color for the lights on the field at 3600K the color looks very natural.

enter image description here

Again, look at the press box as viewed with the white balance adjusted for the orange lights.

enter image description here

Now look at the same photo with the color temperature of 3600K used for the photo taken on the field's surface applied.

enter image description here

  • If you wanted to exaggerate the effect you could presumably process the image twice with white balance for each of the light types, and combine with layer masks. This would help if the sources weren't as widely separated as in your case (e.g. the top image where the yellow is presumably incandescent and the blue from a monitor). – Chris H Nov 11 '16 at 12:06
  • @ChrisH You wouldn't even need to do that. You could just use an HSL tool to boost the saturation of the two colors. – Michael C Nov 11 '16 at 12:11
  • Probably true, though I'm not sure what that would do to other sources (the image on the monitor in the first image for example). – Chris H Nov 11 '16 at 12:16
  • HSL tools only affect the colors within the range of each color band and have no effect on neighboring or complimentary colors. – Michael C Nov 11 '16 at 12:31
  • @MichaelClark Indeed, I can revert the stadium staircase picture from one version to the other (and vice versa) by selecting the appropriate white balance point (either the yellow reflection next to the bin or the stadium flood light). However, this reciprocity does not seem to apply to the chap with the laptop picture. No appropriate white balance point can be found to revert the picture to normal. Something else/additional must be at play! – Serge Stroobandt Nov 14 '16 at 18:23
4

That is not an effect. That is a trend.

The trend is to use complementary colors, and there is not much room to choose from. It is either green to magenta, yellow to blue or red to cyan.

color circle http://www.otake.com.mx/Apuntes/RGB-CMYK/Chicos/1a-RGB-B.png

In reality that is an orange to blue color grading trend.

In movies it is called color grading, and this specific combination is based on some color theory principles of augmenting the chromatic contrast. This trend is more dramatic on action films, and for example in dark horror films the trend is on the contrary, less saturated colors, specially grays and cold blues (Except red if you expect a gore film.)

Action films: action film posters https://www.google.com/search?q=action+film+posters

Horror movies: horror film posters https://www.google.com/search?q=horror+film+poster

The first image of the question also has a tone mapping, which is a contrasted image from saturated to black. This tone mapping is sometimes called "HDRI" effect or look.

Michael Clark also has a good point, where this specific color combination is based on light temperature. Exaggerating this color hues tries to give a more emotional look, including warmth and cold, which is a basic sensation on us humans, and sometimes triggered psychologically by visual stimulation.

On Gimp you can mask some zones and move or adjust the curves.

Additionally, you can work only on the highlights moving just the upper part of the curves, and on the shadows moving only the dark parts.

But probably a good starting point, as this is a photography forum, to put color gels on some light sources in the first place, or using different temperature light sources, for example, cool and warm fluorescent lamps.

  • Your extremely narrow definition of HDRI is a very shortsighted and limited one. Please see: photo.stackexchange.com/a/80598/15871 – Michael C Nov 14 '16 at 22:38
  • I am NOT defining HDRI at all. A photo of a person is most likely NOT an HDRI but tone mapping. On that same post you linked I say about the misconception of "HDRI look", which is specificly tone mapping, btw. – Rafael Nov 14 '16 at 23:12
  • Tone mapping is one form of HDRI. That's the whole point. The term HDRI was around a long time before digital imaging was. That's what Adams' zone system is: photographing a scene in such a way that by controlling the development time of the negative and tone mapping (i.e. dodging/burning) the print a scene with wider total DR can be depicted on a medium (i.e. photo papers available to Adams) with less total DR. Even the history section of the wikipedia article you linked acknowledges that (although the article as a whole disagrees with itself from one section to the next). – Michael C Nov 14 '16 at 23:29
  • Hum. Actually, that much detail on the HDRI information was not mine. :o) I removed it. – Rafael Nov 15 '16 at 2:43
2

Here's another approach. My test image was taken on a PiCam (camera board for the Raspberry Pi) as part of a timelapse. The camera has a rather wide fixed aperture and a small sensor, so the depth of focus is quite low.

This is the original, as shot. The ambient light is fluorescent, but I picked it because of the monitor vs ambient contrast in the first example image.

As shot image

After processing I have: After processing

The bottom layer of the image is the original, with a white point selected (levels dialogue) from the monitor. The top layer is the same, but with the white point chosen on the benchtop (this is actually grey so this step also increased the overall brightness). The upper layer has a layer mask made from the blue channel of the original, with the contrast increased significantly.

This is what the layers dialogue looks like: layers dialogue

  • I think you should start off by picking as white point the white tube clip in the bottom left of the image. This seems to be the whitest object in the image. – Serge Stroobandt Nov 13 '16 at 22:48
  • 1
    Off topic: What were you "cooking" there with your Raspberry Pi? – Serge Stroobandt Nov 13 '16 at 22:53
  • 1
    @SergeStroobandt you're probably right on the clip. This was a very hasty test over lunch. It's a photocatalysis experiment for cleaning water -- we've been on the Rapsberry Pi official blog which includes the timelapse this still was taken from. – Chris H Nov 14 '16 at 9:00
0

Reverse Engineering

Peter Taylor clearly is onto something, by referencing the L*a*b* colour space. The multiple asterisks refer to the CIE 1976 version of this colour space.

Lab colour space

Decomposing the image of the ham radio operator in this colour space shows evidence of what appears to be serious gating/filtering in the histograms of both the a* (green=0 ↔ red=255) and, more importantly, the b* (blue=0 ↔ yellow=255) channel. (The L* channel is for lightness.)

histogram a channel histogram b channel

In GIMP, this decomposition is obtained by clicking on Colors → Components → Decompose… → Lab.

Please, notice that throughout this exposé, linear histograms will be used as oposed to logarithmic scale histograms. In GIMP, switching between scales is done by hitting the rightmost button right above the histrogram.

Reverting the b* channel

Here is what the b* channel originally looks like.

original b channel

In GIMP, select from the menu Colors → Curves.. and apply the following transfer function on the b* channel. Be careful to operate exclusively on the right side of the linear histogram, which affects only yellow tones.

b channel revert

The reverted b* channel will now look like this. There are less bright spots, indicative of fewer amount of yellow tones in the image.

reverted b channel

Indeed, intermediate recomposing, shows much less yellow. The tent fabric seems to have regained its original colour.

image with b channel reverted

Reverting the a* channel

In the image above, there is still a spot of cyan on the desk and the grass through the open tent window looks unnatural. Both observations indicate that the a* channel also requires remedying, albeit to a lesser extent.

Here is what the a* channel looks like originally. The spot of grass indeed looks exceptionally dark in this channel.

original a channel

Apply the following transfer function on the a* channel values. Again, be careful to operate exclusively on the left side of the linear histogram. Doing so, will affect only the green tones.

a channel revert

The reverted a* channel will now look like this. Both the grass and the desk now show less contrast in this channel.

a channel reverted

Recomposing

Colors → Components → Recompose ends up with this result. Notice how the grass now looks natural and the cyan spot on the desk has disappeared. However, the yellow pad remained bright yellow as did the brass of the lamp stand. The LCD window on the radio is orange, as should be on this radio model. The base of the morse code keyer remained red.

This result could not be obtained simply by chosing a new white balance spot anywhere on the picture, as previously suggested.

reverted image

Direct process

  1. Decompose the image to the L*a*b* colour space.
  2. Apply the inverse of the respective a* and b* transfer curves shown above on the linear histogram. The order of application does not matter in this colour space.
  3. Recompose.

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.