Thanks for the pointer - I've just skimmed the last 2 chapters and looks like a good book but don't think it solves my specific problem (just to give more con

Thanks for the pointer - I've just skimmed the last 2 chapters and looks like a good book but don't think it solves my specific problem (just to give more context, when I said amateur I'm doing this for fun not money, but have previously built an image processing pipeline from raw sensor output and I get the basics of wavelets, Fourier etc ) My specific question is "If I am matching a RAW stereo block (say 8x8 or 16x16 block), for sub-pixel resolution matching from two similar cameras, why (if at all) is it better to use DCT/Fourier matching e.g. matlab normxcorr2 or the elphel guys https://blog.elphel.com/2018/01/complex-lapped-transform-bayer/ https://blog.elphel.com/2018/01/complex-lapped-transform-bay... , rather than try to match in the spatial domain (linear algebra). On writing this I suppose I better look at the H.264 and HEVC algos and see if they work in the frequency or spatial domain when they are looking at sub-pixel matches.