Given that in RGB we can represent 256^3 combinations = 16,777,216 colors, and since the human eye can only distinguish roughly 10,000,000, there is obviously a surplus of 6,777,216 RGB combinations that chromatically are indistinguishable from counterpart colors.
Compression algorithms work on this basis when approximating out spacial difference in color ranges across a frame I believe. With that in mind, how can one reliably compute whether a given color is within a range of ‘similarity’ to another?
Of course, ‘similarity’ will be some kind of arbitrary/tunable parameter that can be tweaked, but this is an approximation anyway. So any pointers, pseudocode, intuitive code samples, resources out there to help me model such a function?
Many thanks for your help
Perceptual color difference can be calculated using the The CIEDE2000 Color-Difference Formula. The CIEDE2000 formula is based on the LCH color space (Luminosity, Chroma, and Hue). LCH color space is represented as a cylinder (see image here).
A less accurate (but more manageable) model, is the CIE76 Color-Difference formula, which is based on the Lab color space ( L*a*b*). There are no simple formulas for conversion between RGB or CMYK values and L*a*b*, because the RGB and CMYK color models are device dependent. The RGB or CMYK values first need to be transformed to a specific absolute color space, such as sRGB or Adobe RGB. This adjustment will be device dependent, but the resulting data from the transform will be device independent, allowing data to be transformed to the CIE 1931 color space and then transformed into L*a*b*. This article explains the procedure and the formulas.