autocorr2d

Version 1.0.0.0 (1.71 KB) by Tristan Ursell
Compute the 2D spatial autocorrelation of a matrix or image using the Wiener - Khintchine Theorem.
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Updated 15 May 2018

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Compute the 2D spatial autocorrelation of a matrix or image I using the Wiener - Khintchine Theorem. The output is the normalized correlation coefficient -1 < C < 1.
The center pixel of A will have C = 1. Using images with odd dimensions will give results that are easier to interpret.
ref: http://mathworld.wolfram.com/Wiener-KhinchinTheorem.html

See detailed examples in the m-file help.

Cite As

Tristan Ursell (2026). autocorr2d (https://www.mathworks.com/matlabcentral/fileexchange/67348-autocorr2d), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2016b
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.0.0.0