我已经在互联网上搜索了很多,但仍然没有找到解决方案。我想要的是将 Matlab 的 ifft2
函数转换为 OpenCV 以获得相同的结果。例如,如果我有一个 10x10
矩阵 A
为:
A =
11 22 33 1 1 1 1 1 1 1
44 55 66 1 1 1 1 1 1 1
77 88 99 1 1 1 1 1 1 1
100 111 122 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
然后在 Matlab 中,调用 ifft2(A)
给我这个:
ans =
9.1600 + 0.0000i 5.4570 + 4.6041i 0.5640 + 4.4443i -1.1170 + 0.7295i 1.0560 - 1.4066i 2.7200 + 0.0000i 1.0560 + 1.4066i -1.1170 - 0.7295i 0.5640 - 4.4443i 5.4570 - 4.6041i
1.7274 + 6.5730i -2.5500 + 5.5266i -3.6046 + 1.6030i -1.0629 - 0.6619i 1.2068 + 0.5078i 0.5758 + 2.1910i -0.9060 + 1.3047i 0.2070 - 0.8463i 3.4605 - 0.4030i 4.7141 + 3.3760i
-3.6507 + 1.1351i -3.2357 - 1.1758i -1.1907 - 1.8927i 0.1292 - 0.6560i -0.3480 + 0.5913i -1.2169 + 0.3784i -0.8219 - 0.3575i 0.2811 + 0.1882i 0.0968 + 1.8925i -1.8722 + 2.6341i
0.6876 - 1.9331i 1.4480 - 0.9227i 0.9832 + 0.1199i 0.0550 + 0.1593i -0.1955 - 0.4607i 0.2292 - 0.6444i 0.3196 - 0.1496i -0.3841 + 0.0821i -1.0290 - 0.6749i -0.5821 - 1.7727i
1.1457 + 1.6084i -0.1392 + 1.7632i -0.8331 + 0.7911i -0.3628 - 0.0938i 0.3857 + 0.0000i 0.3819 + 0.5361i -0.1268 + 0.4468i -0.0493 - 0.2667i 0.8930 - 0.4889i 1.6339 + 0.4186i
-1.6800 + 0.0000i -1.1861 - 0.8618i -0.2800 - 0.8618i 0.0661 - 0.2034i -0.2800 + 0.2034i -0.5600 + 0.0000i -0.2800 - 0.2034i 0.0661 + 0.2034i -0.2800 + 0.8618i -1.1861 + 0.8618i
1.1457 - 1.6084i 1.6339 - 0.4186i 0.8930 + 0.4889i -0.0493 + 0.2667i -0.1268 - 0.4468i 0.3819 - 0.5361i 0.3857 - 0.0000i -0.3628 + 0.0938i -0.8331 - 0.7911i -0.1392 - 1.7632i
0.6876 + 1.9331i -0.5821 + 1.7727i -1.0290 + 0.6749i -0.3841 - 0.0821i 0.3196 + 0.1496i 0.2292 + 0.6444i -0.1955 + 0.4607i 0.0550 - 0.1593i 0.9832 - 0.1199i 1.4480 + 0.9227i
-3.6507 - 1.1351i -1.8722 - 2.6341i 0.0968 - 1.8925i 0.2811 - 0.1882i -0.8219 + 0.3575i -1.2169 - 0.3784i -0.3480 - 0.5913i 0.1292 + 0.6560i -1.1907 + 1.8927i -3.2357 + 1.1758i
1.7274 - 6.5730i 4.7141 - 3.3760i 3.4605 + 0.4030i 0.2070 + 0.8463i -0.9060 - 1.3047i 0.5758 - 2.1910i 1.2068 - 0.5078i -1.0629 + 0.6619i -3.6046 - 1.6030i -2.5500 - 5.5266i
在OpenCV中,我写了如下代码(感谢网络),确实取得了与Matlab相同的结果。
cv::Mat inverseDFT;
cv::Mat planes[] = { cv::Mat_<float>(input), cv::Mat::zeros(input.size(), CV_32F) };
cv::Mat complex;
cv::merge(planes, 2, complex);
cv::idft(complex, inverseDFT, cv::DFT_SCALE | cv::DFT_INVERSE);
到目前为止这很好。 但是,当我使用另一个82x82
大小相同类型和值 的矩阵时,Matlab 的结果与OpenCV 的结果大不相同。这是 Matlab 输出(前两行):
1.0e+05 *
[-0.0000 -9.6761 -4.6365 1.8979 1.4972 -0.0025 0.1037 -0.0919 0.3140 0.0032 0.0195 0.0057 -0.0002 0.0147 -0.0023 0.0088 0.0045 -0.0023 0.0135;
-0.6180 4.6026 1.9042 -1.0747 -0.5034 -0.0088 -0.0466 0.0479 -0.1339 -0.0019 -0.0078 -0.0019 -0.0031 -0.0098 0.0009 -0.0038 -0.0053 0.0034 -0.0070;
....]
这是 OpenCV 结果(前两行):
[15.8347 148.3 15.5297 148.068 15.3074 147.476 15.1266 146.854 14.9336 146.121 14.649 145.361 14.4584 144.357 14.1337 143.344 13.8938 142.052 13.4711 140.892 12.9521 139.762 12.3772 138.7 11.7153 137.773 11.149 136.736 10.6333 136.07 10.0025 135.68 9.35163 135.744 8.37026 136.085 7.51313 136.597 6.65663 137.297 5.84039 138.144 5.08981 138.964 4.2696 139.838 3.93125 140.847 3.83195 141.894 4.0224 142.883 4.54194 143.872 5.35709 144.933 6.18112 145.637 6.97564 146.306 7.91474 146.833 8.90979 147.268 9.90416 147.69 10.7855 147.929 11.9145 148.177 13.3188 148.587 14.5545 148.747 15.3029 148.96 15.8501 149.022 16.1713 149.002 16.0789 148.678 ;
83.1579 -72.1501 83.2033 -72.3991 83.0443 -72.9689 83.028 -73.201 82.9732 -73.2787 82.9527 -73.2777 83.039 -73.2688 83.2974 -73.331 83.7781 -73.6298 84.5012 -73.8774 85.2545 -74.02 86.2663 -74.1823 87.4866 -74.3593 88.8467 -74.474 90.3635 -74.5438 91.6828 -74.5036 92.9061 -73.9815 93.1934 -73.0743 93.4254 -72.1992 93.1917 -71.2198 92.45 -70.201 91.1874 -69.4783 89.0805 -68.5612 87.2752 -67.461 85.2434 -66.3476 83.1033 -65.316 80.9829 -64.4404 79.0108 -63.7758 77.3056 -63.3485 75.7612 -63.1322 74.7189 -63.3549 74.1633 -63.9313 74.1057 -64.8886 74.2431 -66.0125 74.9995 -66.9026 76.9265 -67.4861 78.861 -68.5714 80.1996 -69.2898 81.3412 -70.1617 82.2211 -70.9372 82.7735 -71.4485;
....]
是什么造成了这种差异?有人可以帮忙吗?谢谢。
最佳答案
其实Matlab中的fft是离散傅里叶变换, 我发现通过 OpenCV 的 dct 可以达到相同的输出。
关于c++ - OpenCV 中的 Matlab fft2 函数,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/31402963/