Python - Normalized cross-correlation to measure similarites in 2 images

1. How to calculate correlation coefficient between two images in Python?
2. What is normalized cross-correlation in image processing?
3. How do you calculate normalized cross-correlation?

How to calculate correlation coefficient between two images in Python?

All Answers (3)

This function is used to compute the correlation (coefficient) between two pictures (matrices): r = corr2(A,B) computes the correlation coefficient between A and B, where A and B are identical matrices or vectors.

What is normalized cross-correlation in image processing?

Normalized Cross-Correlation (NCC) is by definition the inverse Fourier transform of the convolution of the Fourier transform of two (in this case) images, normalized using the local sums and sigmas (see below).

How do you calculate normalized cross-correlation?

Normalized cross-correlation can detect the correlation of two signals with different amplitudes: norma_corr(a, a/2) = 1. Notice we have perfect correlation between signal A and the same signal with half the amplitude!