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| p.2 #7 · Bayer masks and DxO color depth measurements |
There are a few different (but all interconnected) discussions going on here - at the same time.
But the original question, "Color Depth": This metric as per DxO definition is VERY convoluted unless you have quite a thorough mathematical understanding of both how a tristimuli color representation works, and how noise-covariance step integration works.
But basically it is the numerical count of [with statistical accuracy!] separable colors that the sensor can distinguish at the given ISO, given in log2 format (bits)
This is based on the uncertainty that noise gives. If a sensor has very low levels of noise, uncertainty and the noise covariance diameter decreases, so the next color that is "definitely not the same" lies closer. More noise means that you have to move away further in color before you can say that the color has actually changed.
If the camera's color filters are very weak (like in a compact camera or cellphone) then colors have to be boosted - and this boost amplifies noise by exactly as much as it amplifies saturation.
Imagine a small marble of color. The size (diameter) of the marble indicates how much noise that exact color is affected by. The noise (diameter) is photon shot noise + electronic noise, multiplied by the amount of color boost needed. The marble next to this one has to be at least one diameter away to fit, and it has its' own diameter as calculated for its' own center color. And so on.
Given that you have a marble bag (color space) that is "this big", how many marbles will fit into that bag? That is the color depth. Less noise, less color boost needed = smaller marbles = more marbles will fit into the same bag.
This has nothing (except by necessary cooperation - you can't have one without the other!) to do with color accuracy per se, it's just a measurement of how many colors the camera can distinguish from any other color within its' working gamut.
MDFB's often have very good (to good!) color separation, but often not that brilliant DR - and their over-the-top color separation needs tempering to conform to human vision. But when you combine very good color separation with very low mid-gray noise levels (something MDFB's are extremely good at, but isn't directly related to DR!), you get really impressive gradation possibilities. It may not be perfectly translated into human-vision color, but it does look impressive.
Color accuracy on the other hand, is more about matching camera color to human vision color. Here DxO uses metameric indexes as in ISO standard 17321. This uses ONLY linear math to try and match camera raw's to human vision. It is a measurement of how well you can fit the CFA filters to the human eye response, without resorting to spot color corrections.
But spot color corrections are part of almost any camera more advanced than a cell-phone module nowadays, so the SMI should be taken with a big lump of salt. It doesn't tell that much about the camera, and it certainly does not tell if the errors produced are good-natured (easy to correct with spot color corrections) or pure metameric failures that are impossible to correct.
A camera with an SMI of 80 can be WORSE than a camera with an SMI of 75, if the errors are in sensitive colors and if they are incorrigible.
But a camera with SMI80 will almost certainly be a lot better than the camera with SMI60.