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I'm currently performing matrix cross correlation in python using :

C = scipy.signal.correlate2d(A,A)

where A is a 2D matrix, typically a picture. As you can imagine, it gets very long for large array, such that I'm looking for something faster.

Any hint ? I also heard about scipy.signal.fftconvolve. Despite that it's much more rapid, it rarely give me the same result at the end.

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  • $\begingroup$ my incantation is to ask why do you want to form a large rank 1 matrix? $\endgroup$ – Stanley Pawlukiewicz Jul 17 '18 at 14:36
  • $\begingroup$ Could you say what's A? Is it a 1D signal? Is a Random Vector Process? $\endgroup$ – Royi Jul 17 '18 at 14:57
  • $\begingroup$ A is a 2D - matrix. Typically, it can be an picture. $\endgroup$ – Liris Jul 17 '18 at 17:02
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scipy.signal.correlate2d(A,A) and scipy.signal.fftconvolve(A,A[::-1, ::-1]) will give the same result. The second one is much, much faster.

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