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

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.