[英]Matlab's ifft2 function in OpenCV
我已经在互联网上进行了很多搜索,但仍未找到解决方案。 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
:
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)
给我以下信息:
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,我编写了以下代码(感谢Internet), 实际上实现了与 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 ,当我使用另一个具有相同类型和值的大小为82x82
的矩阵时,Matlab的结果与OpenCV的结果有很大不同。 这是Matlab的输出(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;
....]
是什么导致了这种差异? 有人可以帮忙吗? 谢谢。
实际上,在Matlab中fft是离散傅里叶变换,我发现可以通过OpenCV的dct达到相同的输出
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.