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Color is not physics, confusingly. The 'eye sensitivity response' mode is a color space. But it has problems. Notably, it can represent a lot of impossibly pur

by rocqua 5y ago

Color is not physics, confusingly. The 'eye sensitivity response' mode is a color space. But it has problems. Notably, it can represent a lot of impossibly pure colors (because e.g. your red detectors have a lot of overlap with green so pure red acitivation is impossible). More relevantly, a linear interpretation of this system does not match what people see. Perceived brightness is close to logarithmic. If the cell has double the activation, that looks like a constant increase in brightness. Finally, the way we see color depends on the context, mostly the ambient light. This is largely (but not completely) captured by the idea of color-temperature / a white point. But there are also optical illusion effects around brightness and color.

kloch 5y ago
Color vision is much more complicated and “RGB” doesn’t work the way than most people think it does. The spectral response of the L and M cones mostly overlaps and our perception of color relies heavily on “adversarial” transformations in the brain. The result is a very different effective spectral response superficially resembling RGB bandpass filters except the red channel takes negative values (!) at some wavelengths: https://en.m.wikipedia.org/wiki/CIE_1931_color_space https://en.m.wikipedia.org/wiki/CIE_1931_color_space The negative values can be thought of as requiring additional anti-red (green+blue) to render the correct color. The CIEXYZ color space was invented to address the negative values and also conveniently separate luminance from color information. It is widely used today to do color space transformations since it represents standard human color vision in a reasonably convenient and intuitive way. On a side note, wide band RGB or Bayer filters used in digital cameras are a poor match for the CIE 1931 standard observer effective band pass filters (even ignoring the negative red values). They would result in low saturation colors if mapped directly to a full-gamut RGB colorspace. Conveniently or coincidentally they work well when directly mapped to a limited gamut sRGB color space. Narrower bandpass filters approximating the CIE1931 curves look correct when mapped to a wide gamut like rec.2020. The point is you cannot make simple assumptions about RGB colors at any point in the process. The biggest problem we have today however is many systems are not aware of colorspaces and assume that RGB values are an absolute and invariant encoding of color.

by rocqua 5y ago

kloch 5y ago

Color vision is much more complicated and “RGB” doesn’t work the way than most people think it does. The spectral response of the L and M cones mostly overlaps and our perception of color relies heavily on “adversarial” transformations in the brain. The result is a very different effective spectral response superficially resembling RGB bandpass filters except the red channel takes negative values (!) at some wavelengths: https://en.m.wikipedia.org/wiki/CIE_1931_color_space https://en.m.wikipedia.org/wiki/CIE_1931_color_space The negative values can be thought of as requiring additional anti-red (green+blue) to render the correct color. The CIEXYZ color space was invented to address the negative values and also conveniently separate luminance from color information. It is widely used today to do color space transformations since it represents standard human color vision in a reasonably convenient and intuitive way. On a side note, wide band RGB or Bayer filters used in digital cameras are a poor match for the CIE 1931 standard observer effective band pass filters (even ignoring the negative red values). They would result in low saturation colors if mapped directly to a full-gamut RGB colorspace. Conveniently or coincidentally they work well when directly mapped to a limited gamut sRGB color space. Narrower bandpass filters approximating the CIE1931 curves look correct when mapped to a wide gamut like rec.2020. The point is you cannot make simple assumptions about RGB colors at any point in the process. The biggest problem we have today however is many systems are not aware of colorspaces and assume that RGB values are an absolute and invariant encoding of color.