fft的反fft未返回预期数据

时间:2014-03-25 03:16:16

标签: c++ opencv fft fftw ifft

我正在努力确保FFTW完成我认为它应该做的事情,但我遇到了问题。我正在使用OpenCV的cv::Mat。我制作了一个测试程序,给定了一个Mat f,计算ifft(fft(f))并将结果与​​f进行比较。我希望两者之间的差异可以忽略不计,但数据中有一个奇怪的模式..

在这种情况下,f被初始化为8x8浮点数组,其正值小于1.

这是我的测试程序代码:

Mat f = .. //populate f
if (f.type() != CV_32FC1)
    DLOG << "Bad f type";
const int y = f.rows;
const int x = f.cols;
double* input = fftw_alloc_real(y * 2*(x/2 + 1));
// forward fft
fftw_plan plan = fftw_plan_dft_r2c_2d(x, y, input, (fftw_complex*)input, FFTW_MEASURE);
// inverse fft
fftw_plan iplan = fftw_plan_dft_c2r_2d(x, y, (fftw_complex*)input, input, FFTW_MEASURE);

// populate fftw data from f
for (int yi = 0; yi < y; ++yi)
{
    const float* yptr = f.ptr<float>(yi);
    for (int xi = 0; xi < x; ++xi)
        input[yi*x + xi] = (double)yptr[xi];
}

fftw_execute(plan); 
fftw_execute(iplan);

// put data into another cv::Mat for comparison
Mat check(y, x, f.type());
for (int yi = 0; yi < y; ++yi)
{
    float* yptr = check.ptr<float>(yi);
    for (int xi = 0; xi < x ; ++xi)
        yptr[xi] = (float)input[yi*x + xi];
}

DLOG << Util::summary(f, "f");
DLOG << f;
DLOG << Util::summary(check, "check");
DLOG << check;
Mat diff = f*x*y - check;
DLOG << Util::summary(diff, "diff");
DLOG << diff;

DLOG是我的记录器,Util::summary(cv::Mat m)只打印传递的字符串以及垫子的尺寸,通道,最小值和最大值。

以下是数据的外观(输出):

f: rows:8 cols:8 chans:1 min:0.00257996 max:0.4  
[0.050668437, 0.04509116, 0.033668514, 0.10986148, 0.12855141, 0.048241843, 0.12613985,.09731093;  
0.028602425, 0.0092236707, 0.037089188, 0.118964, 0.075040311, 0.40000001, 0.11959606, 0.071930833;  
0.0025799556, 0.051522054, 0.22233701, 0.052993439, 0.032000393, 0.12673819, 0.015244827, 0.044803992;  
0.13946071, 0.019708242, 0.0112687, 0.047459811, 0.019342113, 0.030085485, 0.018739942, 0.0098618753;  
0.041809395, 0.029681522, 0.026837418, 0.16038358, 0.29034778, 0.17247421, 0.1789207, 0.042179305;  
0.025630442, 0.017192598, 0.060540862, 0.1854037, 0.21287154, 0.04813192, 0.042614728, 0.034764063;  
0.0030835248, 0.018511582, 0.0071733585, 0.017076733, 0.064545207, 0.0026390438, 0.088922881, 0.045725599;
0.12798512, 0.23215951, 0.027465452, 0.03174505, 0.04352935, 0.025079668, 0.044403922, 0.035459157]

check: rows:8 cols:8 chans:1 min:-3.26489 max:25.6  
[3.24278, 2.8858342, 2.1547849, 7.0311346, 8.2272902, 3.0874779, 8.0729504, 6.2278996;  
0.30818239, 0, 2.373708, 7.6136961, 4.8025799, 25.6, 7.6541481, 4.6035733;  
0.16511716, 3.2974114, -3.2648909, 0, 2.0480251, 8.1112442, 0.97566891, 2.8674555;  
8.9254856, 1.2613275, 0.72119683, 3.0374279, -0.32588482, 0, 1.1993563, 0.63116002;  
2.6758013, 1.8996174, 1.7175947, 10.264549, 18.582258, 11.038349, 0.042666838, 0;  
1.6403483, 1.1003263, 3.8746152, 11.865837, 13.623778, 3.0804429, 2.7273426, 2.2249;  
0.44932228, 0, 0.45909494, 1.0929109, 4.1308932, 0.16889881, 5.6910644, 2.9264383;  
8.1910477, 14.858209, -0.071794562, 0, 2.7858784, 1.6050987, 2.841851, 2.2693861]  

diff: rows:8 cols:8 chans:1 min:-0.251977 max:17.4945  
[0, 0, 0, 0, 0, 0, 0, 0;  
1.5223728, 0.59031492, 0, 0, 0, 0, 0, 0;  
0, 0, 17.494459, 3.3915801, 0, 0, 0, 0;  
0, 0, 0, 0, 1.5637801, 1.9254711, 0, 0;  
0, 0, 0, 0, 0, 0, 11.408258, 2.6994755;  
0, 0, 0, 0, 0, 0, 0, 0;  
-0.2519767, 1.1847413, 0, 0, 0, 0, 0, 0;  
0, 0, 1.8295834, 2.0316832, 0, 0, 0, 0]

对我来说困难的部分是diff矩阵中的非零条目。我已经考虑了FFTW对实际数据上就地fft所需的值和填充的缩放;我错过了什么?

我发现令人惊讶的是,当有太多零时,数据可能会被值17(这是最大值的66%)关闭。此外,数据不规则似乎形成对角线图案。

1 个答案:

答案 0 :(得分:0)

正如您在写fftw_alloc_real(y * 2*(x/2 + 1));时所注意到的那样,fftw需要在x方向上留出额外空间来存储复杂数据。在您的情况下,当x = 8时,它需要2*(x/2+1)=10个实数。

http://www.fftw.org/doc/Real_002ddata-DFT-Array-Format.html#Real_002ddata-DFT-Array-Format

所以......你应该在填充input数组或从中获取retreive值时注意这一点。

你改变方式

 input[yi*x + xi] = (double)yptr[xi];

 int xfft=2*(x/2 + 1);
 ...
 input[yi*xfft + xi] = (double)yptr[xi];

 yptr[xi] = (float)input[yi*x + xi];

 yptr[xi] = (float)input[yi*xfft + xi];

它应该解决你的问题,因为你的差异中的非零点对应于额外的填充。

再见,