Slashdot Mirror
Scaling Algorithm Bug In Gimp, Photoshop, Others
Wescotte writes "There is an important error in most photography scaling algorithms. All software tested has the problem: The Gimp, Adobe Photoshop, CinePaint, Nip2, ImageMagick, GQview, Eye of Gnome, Paint, and Krita. The problem exists across three different operating systems: Linux, Mac OS X, and Windows. (These exceptions have subsequently been reported — this software does not suffer from the problem: the Netpbm toolkit for graphic manipulations, the developing GEGL toolkit, 32-bit encoded images in Photoshop CS3, the latest version of Image Analyzer, the image exporters in Aperture 1.5.6, the latest version of Rendera, Adobe Lightroom 1.4.1, Pixelmator for Mac OS X, Paint Shop Pro X2, and the Preview app in Mac OS X starting from version 10.6.) Photographs scaled with the affected software are degraded, because of incorrect algorithmic accounting for monitor gamma. The degradation is often faint, but probably most pictures contain at least an array where the degradation is clearly visible. I believe this has happened since the first versions of these programs, maybe 20 years ago."
Most scaling algorithms treat brightness as a linear space, so e.g. if you're doing downscaling to 1/2 the size in each dimension, collapse 4 pixels into 1 by setting the 1 pixel to the numerical average of the original 4 pixels. But, most images are displayed with an assumption that brightness is a nonlinear space, i.e. gamma > 1. Therefore, scaling changes the perceived brightness, an unexpected result.
10 PRINT CHR$(205.5+RND(1)); : GOTO 10
Excellent point. Just to be safe though, I'm going to take another look through my porn crypt to see if that's true.
BRB.
Well, I am SURE glad I'm using Linux^H^H^H^H^HWindows^H^H^H^H^H^H^HMac^H^H^Hshit.
It is pitch black. You are likely to be eaten by a grue.
I've been telling people for years that I look better in person.
I told them that there's something wrong with pictures of me.
HA!
Now I know.
It's the Scaling Algorithm BUG!
The data in the pictures is not linear data. It assumes that it will be displayed on a system that introduces a gamma of 2.2. (If your display system does not do that physically, it should correct for this.) That is, a gray 127 should not display as halfway between a white 255 and a black zero, in terms of light output. (It should *appear* halfway between them visually, because your eyes aren't linear — that's (part of) why gamma is in use in the first place.) So, a checkerboard pattern of white / black squares will have half the luminosity of the white squares. When scaling down, software will turn it into a bunch of gray pixels. But they should be gray pixels of value 186, not 127.
The page is not well written, but his example images make the issue very clear. It's not about your monitor gamma; it's about the "standard gamma" that all image files assume your monitor has.
But most people who use images expect to look at them eventually. And most image files are meant to be viewed at gamma 2.2. (Printer drivers will at least approximately emulate a gamma of 2.2, and LCDs emulate it intentionally.) If you view the image at some other gamma, you don't see quite what was intended.
Another way of looking at it is that most standard image formats are stored with a nonlinear representation, and people who do math should realize that. For an untagged image, gamma=2.2 is a good bet. gamma=1.0 is a terrible bet.
Of course, if we really want our software to do a good job, then that software should be aware that specifying colors like #FF0000 isn't a good idea -- they look very different on different screens. What the user probably meant to do was specify a particular color, which means that the numbers need to be marked with a color space. (For a great demo, get an HP LP2475w or some other good wide-gamut display, don't install a profile, and look at anyone's photo album. Everyone looks freakishly red-faced.)
I am sure the Chinese government prefers the current implementation.
Actually, any well-specified file format will specify the gamma. Not all allow you to set it per-file, but they do specify it. Normally this is a line in the spec that reads something like "color values use the sRGB color space" or similar — which specifies a gamma of 2.2 (roughly). And sRGB with it's nearly 2.2 gamma has become so standard that assuming anything else (in the absence of a clear spec) would be idiotic.
Ok, so he made a very informative page about it, but this is still a well known effect. It affects practically everything you can do in image editing. Blurs, etc. Most people neither notice nor care. It's rooted in the fact that most images come with undefined black and white points and a gamma chosen for artistic effect rather than physical accuracy. Thus correctly converting to linear gamma is hardly ever possible. You can still correct for monitor gamma to avoid some rarely seen inconsistencies and artifacts, but most people don't even notice, so why bother? However, Photoshop does have everything you need to avoid the effect completely, even in the ancient Photoshop 6.0.
Here's how to properly resize in Photoshop:
1. Convert mode to 16 bit (to avoid tone aliasing in the next step, no other influence on the calculations)
2. Convert to profile, select "Custom RGB", set Gamma to 1.0 (this converts the internal image data to linear gamma, no visible change because the image is color managed and corrected back to monitor gamma on the fly)
3. Image Size
4. Convert to profile, select "Custom RGB", set Gamma to 2.2 (default)
5. Convert mode to 8 bit
Done. You can substitute your favorite image filter for the image resize. Unsharp mask works much better at gamma 1.0, for example. Of course you can use several filters before converting back to monitor gamma and 8 bit.
Well?
It seems crazy to me to embed a particular Gamma value into an image. ...In fact it seems so crazy I must be missing something. Am I?
The article actually touches on this point. The sensitivity of the human eye isn't linear. If you use a linear scale to store luminosity information for an image, you waste a lot of bit depth at high luminosities - the eye has difficulty distinguishing between very bright and very bright plus a little tiny bit. On the other hand, the eye is very good at telling the difference between very dark and black. You need a lot of finely-graduated steps at low luminosity or else your shadows get jaggy.
If you uniformly (linearly) space out luminosities on an 8-bit (256-shade) scale, you store a lot of uninteresting information at the high end, and lose out on visible detail at the low end. A scale with gamma of 2.2 (typical these days) fits a full twenty-eight grey values between 0 and 1 on our hypothetical linear scale. To maintain that kind of luminosity resolution (down where it matters), you'd have to store an extra five bits on your linear scale. An extra sixty percent costs.
~Idarubicin
Well?
Somehow I don't think you've given him enough time.
Several people have spoken about "linear" RGB. That's nice and gets rid of some small level of distortion introduced by the non-linearity. However, it only starts there. For example, the eye sees R, G, and B differently. It is more sensitive to green than red, and to red more than blue, but it's not even that simple as the equations in your eye's processor are much more complicated. Many algorithms that treat the three "equally" are going to change the perceptual mixture. One can use other color spaces, such as HSV, Yuv, xyY, etc. with different advantages and disadvantages
Sound makes a good analogy. When you play music through any given combination of source, amp and speakers, it sounds different. Sometimes we actually like a particular type of sonic "distortion". It's never exactly like the "original" live music, though.
Likewise, any graphics manipulation is "distorting" the original. In fact, when I take a digital image and run it through Lightroom, do a range expansion/equalization, and do a bunch of tweaks to make the image look good, I'm making much larger changes than those little scaling problems listed in the article. The point is, do you think the result looks good?
There's other important variables, such as what colors are next to other colors in the image, how long you look at the image, what else is around you, how tired you are, etc. There's no such thing as color fidelity, there's only approximations to it. Color is hard, and I mean, really hard. See Hunt, "The Reproduction of Colour", or any number of other fine texts to learn more.
Join the window installer's union, where prosperity is a brick throw away!
He seems to take it seriously.
Probably a gamma nazi...
Brain surgery - it's not rocket science!