7 ms·

Ugh. We don't have an entirely clear picture of how our eyes physically detect color, much less how we perceive it, but there are serious problems with the argu

Ugh. We don't have an entirely clear picture of how our eyes physically detect color, much less how we perceive it, but there are serious problems with the argument the author makes here. You cannot simply take a color photograph of a scene, split it in to three channels, then point out that the blue channel is "dark and contains less detail" as evidence of our inability to perceive the color blue. The fact is that the blue channel really is darker because of the actual lack of blue light in the photo. The trick here is that the areas that have a lot of detail (her face, for example) contain less blue. If you use a color meter to inspect the areas around the girls face, you'll find that there is less blue light present. That makes sense, considering that our skin doesn't contain a lot of blue pigment. This fact is exacerbated by the fact that the author overlaps the channel samples in a way that places emphasis on the areas impacted the most. Basically, the author fails to understand the additive color model. We don't notice the pixelation of the blue channel in this photo because the result of the alteration is to introduce a low-contrast color in to the photo where the aberration overlaps: yellow. If you look closely, you'll see that the areas where you see cyan and magenta in the red and green channels are replaced by yellow in the corresponding blue channel alteration. The effects are diminished by two factors: there isn't much blue luminance present to influence the other colors, and yellow contrasts poorly with most of the colors in the photo where we notice it (the hood is white). If you were to take a color-neutral photograph and split out the RGB channels, you'd perceive the same level of detail in all channels. EDIT: I'd kind of like to take back that last statement about perceiving the same level of detail in all channels. I don't know that you would, but that's not the primary thing that bugs me about the author's argument. My main point is that his argument is flawed, not his assertion. I don't know enough about human color perception to make that argument.

bradleyland 16y ago
Anyone curious about how I know there is less blue in the photo should open the photograph in an image editor and inspect the histogram for each channel. If you don't understand color histograms, read my dandy article on the topic: http://upload.bradlanders.com/mycanikon/essays/histograms/html/ http://upload.bradlanders.com/mycanikon/essays/histograms/ht... The article focuses on average luminance, but histograms are interpreted the same for all color channels when looked at individually.
confuzatron 16y ago
Lots of text there, and you certainly sound confident, but I tried an experiment, and it confirmed the claims of the article. I used Paint.NET, loaded in an image, copied it to three layers. Adusted each layer to be a single colour channel, then changed each of the layers to 'Additive' mode. Pixellating the blue layer - I could perceive at most some 'colour blotching', but no real loss of 'sharpness' Pixellating the green layer - pixellation was easily visible. Pixellating the red layer - the effect was somewhere in between. You should give it a try. Here's my test Paint.NET image file with the layers all set up for you: http://dl.dropbox.com/u/714931/bluejay.pdn http://dl.dropbox.com/u/714931/bluejay.pdn
- ramidarigaz 16y ago
  How do you know the unnoticeable pixellation of the blue isn't an artifact of the way blue is displayed by your screen?
  - ivank 16y ago
    If you have an LCD screen with a normal RGBRGB pixel layout, you really can't expect problems. Then again, you can always use a magnifying glass.
  - confuzatron 16y ago
    So, my screen doesn't display blue in a way that pixellation is visible to the human eye, and this is somehow not an issue with the human eye how?
- bradleyland 16y ago
  The additive color model isn't exactly the same as the layer modes you'll see in image editing apps. This "mode" affects how the values of the current layer are applied to the layers below it. The normal mode is to replace the values below. When you switch to additive, the RGB channels from the current layer are "added" to the values of the layer below. This is entirely different than the concept of the additive color model. There are two broad color model types: additive and subtractive. Additive color models (like RGB) "add" color to arrive at white. Subtractive color models (like CMYK) "subtract" color to arrive at white. In the RGB additive color model, we most frequently refer to the primary colors, RGB, but the secondary colors (cyan, magenta, and yellow) are equally important. The primary colors are the result of raising only one channel to full luminance while all the others are at zero. The secondary colors are produced by raising all channels to the maximum, then dropping one channel to zero. The secondary color for the blue channel is yellow. The consequence of this is that you can't simply pixelate the blue channel in an additive model RGB image and claim this proves a lack of ability to perceive color in the blue light spectrum, because the alteration of the primary color will inevitably affect the distribution of the secondary color, depending upon the luminance of the other channels in the region. A better test would display a test pattern in different colors, but matching luminosity. The trouble with testing this on your computer is that your display must be calibrated. On a properly calibrated display, the display of RGB[0,255,0] and RGB[0,0,255] should have identical luminance values. Very few people have calibrated displays, and even if you do, the chances that your display is accurate throughout the color gamut for a given luminance value is even less.
corysama 16y ago
I do know a little about human color perception. Although the author's example is flawed, his argument does stand. Human eyes are much less sensitive to details in blue compared to green and red. Here's the best illustration I can find in a minute's googling: http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/OWENS/LECT14/cones.gif http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/OWEN... from http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/OWENS/LECT14/lecture12.html http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/OWEN... This shows up in the Red-vs-Blue battle analytics in both Halo and Team Fortress 2 --Blue wins measurably more often because they are harder to focus on. Red-vs-Green would be more fair, but that would screw over the large male population with Red-Green colorblindness. This is why the standard conversion of linear RGB to greyscale is 30%red + 59%green + 11%blue. 33% each would make the blue seem to have too much influence after conversion. This is why BluBlocker glasses make the world seem more sharp. It's why I try to minimize blue in my IDE color schemes. If you are designing a purely pragmatic UX that requires seeing fine details, I'd recommend a yellow-on-black color scheme with some green and little blue. The classic green/amber terminal screens of yore were ugly, but effective.
- sliverstorm 16y ago
  > Human eyes are much less sensitive to details in blue compared to green and red IIRC our strength with green is why many night-vision systems use only green. It has other benefits such as not killing your night vision, but when you take the darkness of the night and remove the red and blue components, you can see better. Once again, IIRC.
  - corysama 16y ago
    While looking for the illustration above, I also found this page http://starizona.com/acb/ccd/advtheorycolor.aspx http://starizona.com/acb/ccd/advtheorycolor.aspx with this illustration of "Spectral response of the dark-adapted human eye. Note the lack of red sensitivity." http://starizona.com/acb/ccd/advimages/eyeqenight.jpg http://starizona.com/acb/ccd/advimages/eyeqenight.jpg Compared to the daylight-adapted eye: http://starizona.com/acb/ccd/advimages/eyeqe.jpg http://starizona.com/acb/ccd/advimages/eyeqe.jpg This is interesting news to me.
jemfinch 16y ago
You're wrong. No, you can't just split a picture into three channels and say "Hey, blue looks dark," because blue might actually be dark. You can, however, make a picture grayscale, then turn that same grayscale picture into redscale, greenscale, and bluescale. The luminance would be exactly the same for every pixel, the only difference would be the pixel's color. I did that, in fact, and you know what? Your eyes really do suck at blue: http://www.flickr.com/photos/jemfinch/sets/72157617048178001/ http://www.flickr.com/photos/jemfinch/sets/72157617048178001... We do have a clear enough picture of how our eyes work to know that the blue receptors are far fewer than the red and green receptors. Your eyes suck at blue. My eyes suck at blue. All of our eyes suck at blue. Every time this story comes up, someone brings up this point. That's why I did it right: so I could reply to arrogant comments like yours that assume because an experiment is flawed that the theory it tried to prove must be wrong.
- tensor 16y ago
  Actually, your conclusion is incorrect. While there are fewer receptors for blue, each is much more sensitive. All you demonstrated is that the sRGB color model is blue deficient. See http://en.wikipedia.org/wiki/Color_vision http://en.wikipedia.org/wiki/Color_vision and http://www.ecse.rpi.edu/~schubert/Light-Emitting-Diodes-dot-org/Sample-Chapter.pdf http://www.ecse.rpi.edu/~schubert/Light-Emitting-Diodes-dot-... for details. In particular, I'd like to draw your attention to the CIE 1931 chromatic diagram in the wikipedia link. This is supposed to represent the visible spectrum that the eye can see. The triangle is the sRGB colour space, what your monitor can reproduce. Notice how little blue the triangle contains? This is why your blue image looks so dark. From the second link, it also turns out that CIE 1931 actually underestimates blue sensitivity. The book chapter discusses a corrected version called CIE 1978. It also has a plot of the eye sensitivity to various wavelengths. It turns out that our eyes are about as good at both blue and red, but more sensitive to green and yellow. Experimentation is difficult. There are often a lot of factors you need to consider. Also, may I ask that you be a little less confrontational in the future? It's quite unnecessary. The majority of people here have good intentions. edit: upon further research, it turns out it's even more complicated than just the sensitivity and cone numbers. Here: http://hyperphysics.phy-astr.gsu.edu/hbase/vision/rodcone.html#c3b http://hyperphysics.phy-astr.gsu.edu/hbase/vision/rodcone.ht... it states that we should still have less sensitivity to blue. However, we do perceive it to be the same intensity despite this. It appears that we do have difficulty determining details from blue objects, though. The reason is that most of the blue receptors are on the outer areas of the retina. It is a complex topic apparently.
deleted 16y ago
[deleted]
punchagan 16y ago
Here's a little experiment that I did. http://punchagan.muse-amuse.in/blog/do-our-eyes-suck-at-blue.html http://punchagan.muse-amuse.in/blog/do-our-eyes-suck-at-blue... I tried swapping channels, to cancel any unsymmetric effects like the use of Bayer filter etc. And still I find that the Green channel is always the most pixelated. The difference between Red and Blue channels is not all that perceivable.

bradleyland 16y ago

Anyone curious about how I know there is less blue in the photo should open the photograph in an image editor and inspect the histogram for each channel. If you don't understand color histograms, read my dandy article on the topic: http://upload.bradlanders.com/mycanikon/essays/histograms/html/ http://upload.bradlanders.com/mycanikon/essays/histograms/ht... The article focuses on average luminance, but histograms are interpreted the same for all color channels when looked at individually.

confuzatron 16y ago

Lots of text there, and you certainly sound confident, but I tried an experiment, and it confirmed the claims of the article. I used Paint.NET, loaded in an image, copied it to three layers. Adusted each layer to be a single colour channel, then changed each of the layers to 'Additive' mode. Pixellating the blue layer - I could perceive at most some 'colour blotching', but no real loss of 'sharpness' Pixellating the green layer - pixellation was easily visible. Pixellating the red layer - the effect was somewhere in between. You should give it a try. Here's my test Paint.NET image file with the layers all set up for you: http://dl.dropbox.com/u/714931/bluejay.pdn http://dl.dropbox.com/u/714931/bluejay.pdn

ramidarigaz 16y ago
How do you know the unnoticeable pixellation of the blue isn't an artifact of the way blue is displayed by your screen?
- ivank 16y ago
  If you have an LCD screen with a normal RGBRGB pixel layout, you really can't expect problems. Then again, you can always use a magnifying glass.
- confuzatron 16y ago
  So, my screen doesn't display blue in a way that pixellation is visible to the human eye, and this is somehow not an issue with the human eye how?
bradleyland 16y ago
The additive color model isn't exactly the same as the layer modes you'll see in image editing apps. This "mode" affects how the values of the current layer are applied to the layers below it. The normal mode is to replace the values below. When you switch to additive, the RGB channels from the current layer are "added" to the values of the layer below. This is entirely different than the concept of the additive color model. There are two broad color model types: additive and subtractive. Additive color models (like RGB) "add" color to arrive at white. Subtractive color models (like CMYK) "subtract" color to arrive at white. In the RGB additive color model, we most frequently refer to the primary colors, RGB, but the secondary colors (cyan, magenta, and yellow) are equally important. The primary colors are the result of raising only one channel to full luminance while all the others are at zero. The secondary colors are produced by raising all channels to the maximum, then dropping one channel to zero. The secondary color for the blue channel is yellow. The consequence of this is that you can't simply pixelate the blue channel in an additive model RGB image and claim this proves a lack of ability to perceive color in the blue light spectrum, because the alteration of the primary color will inevitably affect the distribution of the secondary color, depending upon the luminance of the other channels in the region. A better test would display a test pattern in different colors, but matching luminosity. The trouble with testing this on your computer is that your display must be calibrated. On a properly calibrated display, the display of RGB[0,255,0] and RGB[0,0,255] should have identical luminance values. Very few people have calibrated displays, and even if you do, the chances that your display is accurate throughout the color gamut for a given luminance value is even less.

corysama 16y ago

I do know a little about human color perception. Although the author's example is flawed, his argument does stand. Human eyes are much less sensitive to details in blue compared to green and red. Here's the best illustration I can find in a minute's googling: http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/OWENS/LECT14/cones.gif http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/OWEN... from http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/OWENS/LECT14/lecture12.html http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/OWEN... This shows up in the Red-vs-Blue battle analytics in both Halo and Team Fortress 2 --Blue wins measurably more often because they are harder to focus on. Red-vs-Green would be more fair, but that would screw over the large male population with Red-Green colorblindness. This is why the standard conversion of linear RGB to greyscale is 30%red + 59%green + 11%blue. 33% each would make the blue seem to have too much influence after conversion. This is why BluBlocker glasses make the world seem more sharp. It's why I try to minimize blue in my IDE color schemes. If you are designing a purely pragmatic UX that requires seeing fine details, I'd recommend a yellow-on-black color scheme with some green and little blue. The classic green/amber terminal screens of yore were ugly, but effective.

sliverstorm 16y ago
> Human eyes are much less sensitive to details in blue compared to green and red IIRC our strength with green is why many night-vision systems use only green. It has other benefits such as not killing your night vision, but when you take the darkness of the night and remove the red and blue components, you can see better. Once again, IIRC.
- corysama 16y ago
  While looking for the illustration above, I also found this page http://starizona.com/acb/ccd/advtheorycolor.aspx http://starizona.com/acb/ccd/advtheorycolor.aspx with this illustration of "Spectral response of the dark-adapted human eye. Note the lack of red sensitivity." http://starizona.com/acb/ccd/advimages/eyeqenight.jpg http://starizona.com/acb/ccd/advimages/eyeqenight.jpg Compared to the daylight-adapted eye: http://starizona.com/acb/ccd/advimages/eyeqe.jpg http://starizona.com/acb/ccd/advimages/eyeqe.jpg This is interesting news to me.

jemfinch 16y ago

You're wrong. No, you can't just split a picture into three channels and say "Hey, blue looks dark," because blue might actually be dark. You can, however, make a picture grayscale, then turn that same grayscale picture into redscale, greenscale, and bluescale. The luminance would be exactly the same for every pixel, the only difference would be the pixel's color. I did that, in fact, and you know what? Your eyes really do suck at blue: http://www.flickr.com/photos/jemfinch/sets/72157617048178001/ http://www.flickr.com/photos/jemfinch/sets/72157617048178001... We do have a clear enough picture of how our eyes work to know that the blue receptors are far fewer than the red and green receptors. Your eyes suck at blue. My eyes suck at blue. All of our eyes suck at blue. Every time this story comes up, someone brings up this point. That's why I did it right: so I could reply to arrogant comments like yours that assume because an experiment is flawed that the theory it tried to prove must be wrong.

tensor 16y ago
Actually, your conclusion is incorrect. While there are fewer receptors for blue, each is much more sensitive. All you demonstrated is that the sRGB color model is blue deficient. See http://en.wikipedia.org/wiki/Color_vision http://en.wikipedia.org/wiki/Color_vision and http://www.ecse.rpi.edu/~schubert/Light-Emitting-Diodes-dot-org/Sample-Chapter.pdf http://www.ecse.rpi.edu/~schubert/Light-Emitting-Diodes-dot-... for details. In particular, I'd like to draw your attention to the CIE 1931 chromatic diagram in the wikipedia link. This is supposed to represent the visible spectrum that the eye can see. The triangle is the sRGB colour space, what your monitor can reproduce. Notice how little blue the triangle contains? This is why your blue image looks so dark. From the second link, it also turns out that CIE 1931 actually underestimates blue sensitivity. The book chapter discusses a corrected version called CIE 1978. It also has a plot of the eye sensitivity to various wavelengths. It turns out that our eyes are about as good at both blue and red, but more sensitive to green and yellow. Experimentation is difficult. There are often a lot of factors you need to consider. Also, may I ask that you be a little less confrontational in the future? It's quite unnecessary. The majority of people here have good intentions. edit: upon further research, it turns out it's even more complicated than just the sensitivity and cone numbers. Here: http://hyperphysics.phy-astr.gsu.edu/hbase/vision/rodcone.html#c3b http://hyperphysics.phy-astr.gsu.edu/hbase/vision/rodcone.ht... it states that we should still have less sensitivity to blue. However, we do perceive it to be the same intensity despite this. It appears that we do have difficulty determining details from blue objects, though. The reason is that most of the blue receptors are on the outer areas of the retina. It is a complex topic apparently.

deleted 16y ago

[deleted]

punchagan 16y ago

Here's a little experiment that I did. http://punchagan.muse-amuse.in/blog/do-our-eyes-suck-at-blue.html http://punchagan.muse-amuse.in/blog/do-our-eyes-suck-at-blue... I tried swapping channels, to cancel any unsymmetric effects like the use of Bayer filter etc. And still I find that the Green channel is always the most pixelated. The difference between Red and Blue channels is not all that perceivable.