Image error metrics

While developing and refining crunch I used a matrix of statistics like this:

RGB Total   Error: Max:  73, Mean: 17.404, MSE: 176.834, RMSE: 13.298, PSNR: 25.655, SSIM: 0.000000
RGB Average Error: Max:  73, Mean: 5.801, MSE: 58.945, RMSE: 7.678, PSNR: 30.426, SSIM: 0.907993
Luma        Error: Max:  64, Mean: 4.640, MSE: 37.593, RMSE: 6.131, PSNR: 32.380, SSIM: 0.945000
Red         Error: Max:  69, Mean: 5.387, MSE: 52.239, RMSE: 7.228, PSNR: 30.951, SSIM: 0.921643
Green       Error: Max:  70, Mean: 5.052, MSE: 48.298, RMSE: 6.950, PSNR: 31.291, SSIM: 0.934051
Blue        Error: Max:  73, Mean: 6.966, MSE: 76.296, RMSE: 8.735, PSNR: 29.306, SSIM: 0.868285

I computed these stats from a PNG image uploaded by @dougallj showing the progress he's been making on his experimental ETC1 encoder with kodim18, originally from here:

The code that computes this stuff is actually used by the DXT1 front-end to determine how the 8x8 "macroblocks" should be tiled.

The per-channel stuff is useful for debugging, and for tuning the encoder's perceptual RGB weights (which is only used when the compressor is in perceptual mode). Per-channel stats are also useful when trying to get a rough idea what weights a closed source block encoder uses, too.