我试图使用OpenCV而不是fftw,因为OpenCV的许可证更宽松。在的帮助下FFTW fftwf_plan_r2r_2d()与FFTW_REDFT01等效
我意识到目前这是错误的,这只是我最初的想法。我需要一些指导来获得OpenCV的fftw的确切功能,我为能够帮助我做到这一点的人提供奖励。
我只需要那些特定的函数,目前我对转换其他fftw函数不感兴趣。
谢谢!
有人吗?
h:
#pragma once
#define DO_NOT_USE_FFTW
#ifdef DO_NOT_USE_FFTW
enum fftwf_r2r_kind
{
FFTW_R2HC, //computes a real-input DFT with output in “halfcomplex” format, i.e. real and imaginary parts for a transform of size n stored as: r0, r1, r2, ..., rn/2, i(n+1)/2-1, ..., i2, i1 (Logical N=n, inverse is FFTW_HC2R.)
FFTW_HC2R, //computes the reverse of FFTW_R2HC, above. (Logical N=n, inverse is FFTW_R2HC.)
FFTW_DHT, //computes a discrete Hartley transform. (Logical N=n, inverse is FFTW_DHT.)
FFTW_REDFT00, //computes an REDFT00 transform, i.e. a DCT-I. (Logical N=2*(n-1), inverse is FFTW_REDFT00.)
FFTW_REDFT10, //computes an REDFT10 transform, i.e. a DCT-II (sometimes called “the” DCT). (Logical N=2*n, inverse is FFTW_REDFT01.)
FFTW_REDFT01, //computes an REDFT01 transform, i.e. a DCT-III (sometimes called “the” IDCT, being the inverse of DCT-II). (Logical N=2*n, inverse is FFTW_REDFT=10.)
FFTW_REDFT11, //computes an REDFT11 transform, i.e. a DCT-IV. (Logical N=2*n, inverse is FFTW_REDFT11.)
FFTW_RODFT00, //computes an RODFT00 transform, i.e. a DST-I. (Logical N=2*(n+1), inverse is FFTW_RODFT00.)
FFTW_RODFT10, //computes an RODFT10 transform, i.e. a DST-II. (Logical N=2*n, inverse is FFTW_RODFT01.)
FFTW_RODFT01, //computes an RODFT01 transform, i.e. a DST-III. (Logical N=2*n, inverse is FFTW_RODFT=10.)
FFTW_RODFT11, //computes an RODFT11 transform, i.e. a DST-IV. (Logical N=2*n, inverse is FFTW_RODFT11.)
};
struct fftwf_plan_imp
{
int nx;
int ny;
float * in;
float * out;
fftwf_r2r_kind kindx;
fftwf_r2r_kind kindy;
unsigned flags;
};
#define fftwf_plan fftwf_plan_imp *
#define fftwf_malloc(x) malloc(x)
#define fftwf_free(x) free(x)
#define FFTW_DESTROY_INPUT 1
#define FFTW_ESTIMATE 1
fftwf_plan fftwf_plan_r2r_2d(int nx, int ny, float * in, float * out, fftwf_r2r_kind kindx, fftwf_r2r_kind kindy, unsigned flags);
void fftwf_execute(fftwf_plan x);
void fftwf_destroy_plan(fftwf_plan x);
void fftwf_cleanup();
#else
#include <fftw3.h>
#endif
src:
#include "KissInterface.h"
#include "kiss_fftr.h"
#include "kiss_fftndr.h"
#include "opencv.hpp"
//currently cv::dct supports even-size arrays (2, 4, 6 ...). For data analysis and approximation you can pad the array when necessary.
#ifdef DO_NOT_USE_FFTW
fftwf_plan fftwf_plan_r2r_2d(int nx, int ny, float * in, float * out, fftwf_r2r_kind kindx, fftwf_r2r_kind kindy, unsigned flags)
{
fftwf_plan plan = new fftwf_plan_imp;
plan->nx = nx;
plan->ny = ny;
plan->in = in;
plan->out = out;
plan->kindx = kindx;
plan->kindy = kindy;
plan->flags = flags;
return plan;
}
void fftwf_execute(fftwf_plan x)
{
int newx = x->nx;
int newy = x->ny;
if(newx % 2 != 0)++newx;
if(newy % 2 != 0)++newy;
cv::Mat Input (cv::Size(newx, newy), CV_32FC1, x->in); //AUTO_STEP or not?
cv::Mat Output(cv::Size(newx, newy), CV_32FC1, x->out); //AUTO_STEP or not?
if(x->kindx == FFTW_REDFT00 && x->kindy == FFTW_REDFT00)
{
cv::dct(Input, Output);
}
else if(x->kindx == FFTW_REDFT10 && x->kindy == FFTW_REDFT10)
{
cv::dct(Input, Output);
Output *= (4 * sqrt(float(newx / 2)) * sqrt(float(newy / 2)));
Output.row(0) *= 1.41421356237;
Output.col(0) *= 1.41421356237;
}
else if(x->kindx == FFTW_REDFT01 && x->kindy == FFTW_REDFT01)
{
// First re-scale the data for idct():
Input /= (4 * sqrt(float(newx / 2)) * sqrt(float(newy / 2)));
Input.row(0) /= 1.41421356237;
Input.col(0) /= 1.41421356237;
cv::idct(Input, Output); // this will return the input exactly
// However, the transforms computed by FFTW are unnormalized, exactly like the corresponding,
// so computing a transform followed by its inverse yields the original array scaled by N, where N is the logical DFT size.
// The logical DFT size: Logical N=2*n for each axis, this is th implicit symmetrization
// of the image: reflect right and then reflect both halves down.
int logicalSizeN = (2 * newx) * (2 * newy);
Output *= logicalSizeN; // scale to be like FFTW result
}
memcpy(x->out, Output.ptr<float>(0), x->nx * x->ny);
}
void fftwf_destroy_plan(fftwf_plan x)
{
delete x;
x = NULL;
}
void fftwf_cleanup()
{
}
#endif
OpenCV的FFT/DCT与Matlab的实现类似。了解这一点可以帮助你找到更好的参考资料和答案
在我的问答中,你有几个链接可以帮助你开始。
最近,我不得不回到这段代码并对其进行返工,结果发现,由于我想使用转换,然后再转换回来,我可以避免之前和之后的所有额外缩放,而且它很有效
当然,这意味着(变换之间的)中间值与fftw不同,但逆变换后的结果是。