Cross-correlation in frequency domain and xcorr2 in MATLAB
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What are the reasons for the differences between my frequency domain cross-correlation results and those obtained using the xcorr2() function in MATLAB? Is it possible that xcorr2() performs spatial domain cross-correlation, and how might this affect the results?
img1 = imread('1.jpg');
img2 = imread('2.jpg');
img1_gray = rgb2gray(img1);
img2_gray = rgb2gray(img2);
[m, n] = size(img1_gray);
[p, q] = size(img2_gray);
fft_img1 = fft2(img1_gray, m + p - 1, n + q - 1);
fft_img2 = fft2(img2_gray, m + p - 1, n + q - 1);
cross_correlation = (fft_img1 .* conj(fft_img2));
cross_correlation = ifft2(cross_correlation);
cross_correlation = fftshift(cross_correlation);
cross_correlation_xcorr2 = xcorr2(img2_gray, img1_gray);
figure;
subplot(2, 1, 1);
imshow(cross_correlation, []);
title('Custom Cross-Correlation');
subplot(2, 1, 2);
imshow(cross_correlation_xcorr2, []);
title('xcorr2');
Results:
2 件のコメント
Paul
2024 年 5 月 11 日
Can you add 1.jpg and 2.jpg to your post using the Paperclip icon on the Insert menu?
採用された回答
Paul
2024 年 5 月 11 日
Hi Shy,
Assuming that the output of the xcorr2 is the expected result, it can be obtained with the changes below
img1 = imread('1.jpg');
img2 = imread('2.jpg');
img1_gray = rgb2gray(img1);
img2_gray = rgb2gray(img2);
[m, n] = size(img1_gray);
[p, q] = size(img2_gray);
%fft_img1 = fft2(img1_gray, m + p - 1, n + q - 1);
fft_img1 = fft2(flipud(fliplr(img1_gray)), m + p - 1, n + q - 1);
fft_img2 = fft2(img2_gray, m + p - 1, n + q - 1);
%cross_correlation = (fft_img1 .* conj(fft_img2));
cross_correlation = (fft_img1 .* fft_img2);
cross_correlation = ifft2(cross_correlation);
%cross_correlation = fftshift(cross_correlation);
cross_correlation_xcorr2 = xcorr2(img2_gray, img1_gray);
figure;
subplot(2, 1, 1);
imshow(cross_correlation, []);
title('Custom Cross-Correlation');
subplot(2, 1, 2);
imshow(cross_correlation_xcorr2, []);
title('xcorr2');
3 件のコメント
Paul
2024 年 5 月 11 日
As I undersand it, xcorr2(x,y) is the the same as conv2 of x and the 2D-reversed conjugate of y. But in this case, img1_gray is real, so its conjugate is itself. With that understanding, I just made the fft stuff implement the convolution of img2 and the 2D-reverse of img1 (because img1 is the second argument to xcorr2).
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