As far as I can tell, the problem is:
- Simple math works correctly only in a linear color space.
- Images and the rest of web content is 8 bits per channel sRGB.
- Converting between two 8-bit color spaces is lossy.
The proposed solutions are:
- Pass image data as-is to WebGL, treat WebGL canvas values as sRGB. (I.e. the do-nothing solution. If application writers want correct math, they should use linear textures and do a final linear-to-sRGB pass on the rendered image.)
- Optionally convert textures to linear color space, treat WebGL canvas as linear. (Problematic as there is severe information loss at the conversions. Math works correctly though.)
Color spaces? But I thought space was black?
Well, actually, space has no color. It's transparent. It just looks black because there's very little light coming through it at most points.
Color spaces, on the other hand, are definitions of what the numerical pixel values in an image mean. A linear RGB color space means something like "given an output device with three component emitters at wavelengths R=580 nm, G=490 nm and B=440 nm, the number of photons emitted by an emitter is Max_Output * V, where V = component_value / (2^component_bits-1)." For sRGB, the component values are transformed by the sRGB curve (roughly pow(V, 2.2)) to have more control over the important parts of the dynamic range. In particular, sRGB sacrifices precision in the light end to have more control in the darks. Converting linear->sRGB loses detail in the light end, whereas sRGB->linear loses detail in the dark end.
To project an image onto your eyeball, the image data goes through the following wringer: Image data in image color space -> Viewer app color space -> Window system color space -> Display device color space -> Hardware blinkenlichts -> Eyeball.
Now, most software goes "huh?" at the mention of that and acts as if the image data is in the window system color space and uses the data directly. Further, the assumption when doing image editing operations is that the aforementioned color space is linear. (Why that might cause problems is that while 0.25 + 0.25 has the same luminance as 0.5 in a linear color space, to add the luminances in gamma 2.2 you have to do (0.25^2.2 + 0.25^2.2)^(1/2.2) = 0.34.)
Software that requires accurate color handling usually converts the 8-bit values to 16 or 32-bit linear color space to get around the conversion errors and to get easy correct math internally. The resulting high-depth image is then converted down to window system color space for viewing.
The real solution is to use 64 bits per channel and specify the channels to mean photon count / second / mm^2. With that, you can crank from 1 photon / second all the way up to 6500x noon sunlight. And linear math. Then use that as the interchange format between everything. Heyo, massive framebuffers~
In the meantime, maybe the browser could have an iconv-like system for converting images from one color space to another. WebGL 1.0 doesn't have float textures, so upconverting to linear float textures has to wait for the float texture extension.
With linear float textures, you could upconvert all images to float textures, then use a linear float FBO for rendering, and finally convert the FBO to sRGB to display on the canvas element.