本文介绍了在openCV中的小波变换的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
有人试图在opencv或C ++中实现DWT吗？
我看到这个主题的旧帖子，我没有发现它们对我有用，因为我需要一个近似系数和细节作为小波变换的结果。
did someone tried to implement DWT in opencv or in C++?I saw older posts on this subject and i didn't find them useful for me, because I need a approximation coefficient and details as a result of wavelet transformation.
我试图将此（）添加到我的项目，但它不工作，以及计划。
I tried to add this (http://wavelet2d.sourceforge.net/) to my project but it's not working as well as planned.
这是简单的，因为结果参数我需要近似系数和细节：
And this is to simple, because as a result parameters i need approximation coefficient and details:
void haar1(float *vec, int n, int w)
{
int i=0;
float *vecp = new float[n];
for(i=0;i<n;i++)
vecp[i] = 0;
w/=2;
for(i=0;i<w;i++)
{
vecp[i] = (vec[2*i] + vec[2*i+1])/sqrt(2.0);
vecp[i+w] = (vec[2*i] - vec[2*i+1])/sqrt(2.0);
}
for(i=0;i<(w*2);i++)
vec[i] = vecp[i];
delete [] vecp;
}
void haar2(float **matrix, int rows, int cols)
{
float *temp_row = new float[cols];
float *temp_col = new float[rows];
int i=0,j=0;
int w = cols, h=rows;
while(w>1 || h>1)
{
if(w>1)
{
for(i=0;i<h;i++)
{
for(j=0;j<cols;j++)
temp_row[j] = matrix[i][j];
haar1(temp_row,cols,w);
for(j=0;j<cols;j++)
matrix[i][j] = temp_row[j];
}
}
if(h>1)
{
for(i=0;i<w;i++)
{
for(j=0;j<rows;j++)
temp_col[j] = matrix[j][i];
haar1(temp_col, rows, h);
for(j=0;j<rows;j++)
matrix[j][i] = temp_col[j];
}
}
if(w>1)
w/=2;
if(h>1)
h/=2;
}
delete [] temp_row;
delete [] temp_col;
}
因此，有人可以帮我找到在C ++中实现的dwt或指向我如何提取从上面的代码系数。感谢
So can someone help me find dwt implemented in C++ or point me how to extract from above code coefficients. Thanks
推荐答案
这里是直接和逆Haar小波变换（用于过滤）：
Here is direct and inverse Haar Wavelet transform (used for filtering):
#include "opencv2/opencv.hpp"
#include <iostream>
#include <vector>
#include <stdio.h>
using namespace cv;
using namespace std;
// Filter type
#define NONE 0 // no filter
#define HARD 1 // hard shrinkage
#define SOFT 2 // soft shrinkage
#define GARROT 3 // garrot filter
//--------------------------------
// signum
//--------------------------------
float sgn(float x)
{
float res=0;
if(x==0)
{
res=0;
}
if(x>0)
{
res=1;
}
if(x<0)
{
res=-1;
}
return res;
}
//--------------------------------
// Soft shrinkage
//--------------------------------
float soft_shrink(float d,float T)
{
float res;
if(fabs(d)>T)
{
res=sgn(d)*(fabs(d)-T);
}
else
{
res=0;
}
return res;
}
//--------------------------------
// Hard shrinkage
//--------------------------------
float hard_shrink(float d,float T)
{
float res;
if(fabs(d)>T)
{
res=d;
}
else
{
res=0;
}
return res;
}
//--------------------------------
// Garrot shrinkage
//--------------------------------
float Garrot_shrink(float d,float T)
{
float res;
if(fabs(d)>T)
{
res=d-((T*T)/d);
}
else
{
res=0;
}
return res;
}
//--------------------------------
// Wavelet transform
//--------------------------------
static void cvHaarWavelet(Mat &src,Mat &dst,int NIter)
{
float c,dh,dv,dd;
assert( src.type() == CV_32FC1 );
assert( dst.type() == CV_32FC1 );
int width = src.cols;
int height = src.rows;
for (int k=0;k<NIter;k++)
{
for (int y=0;y<(height>>(k+1));y++)
{
for (int x=0; x<(width>>(k+1));x++)
{
c=(src.at<float>(2*y,2*x)+src.at<float>(2*y,2*x+1)+src.at<float>(2*y+1,2*x)+src.at<float>(2*y+1,2*x+1))*0.5;
dst.at<float>(y,x)=c;
dh=(src.at<float>(2*y,2*x)+src.at<float>(2*y+1,2*x)-src.at<float>(2*y,2*x+1)-src.at<float>(2*y+1,2*x+1))*0.5;
dst.at<float>(y,x+(width>>(k+1)))=dh;
dv=(src.at<float>(2*y,2*x)+src.at<float>(2*y,2*x+1)-src.at<float>(2*y+1,2*x)-src.at<float>(2*y+1,2*x+1))*0.5;
dst.at<float>(y+(height>>(k+1)),x)=dv;
dd=(src.at<float>(2*y,2*x)-src.at<float>(2*y,2*x+1)-src.at<float>(2*y+1,2*x)+src.at<float>(2*y+1,2*x+1))*0.5;
dst.at<float>(y+(height>>(k+1)),x+(width>>(k+1)))=dd;
}
}
dst.copyTo(src);
}
}
//--------------------------------
//Inverse wavelet transform
//--------------------------------
static void cvInvHaarWavelet(Mat &src,Mat &dst,int NIter, int SHRINKAGE_TYPE=0, float SHRINKAGE_T=50)
{
float c,dh,dv,dd;
assert( src.type() == CV_32FC1 );
assert( dst.type() == CV_32FC1 );
int width = src.cols;
int height = src.rows;
//--------------------------------
// NIter - number of iterations
//--------------------------------
for (int k=NIter;k>0;k--)
{
for (int y=0;y<(height>>k);y++)
{
for (int x=0; x<(width>>k);x++)
{
c=src.at<float>(y,x);
dh=src.at<float>(y,x+(width>>k));
dv=src.at<float>(y+(height>>k),x);
dd=src.at<float>(y+(height>>k),x+(width>>k));
// (shrinkage)
switch(SHRINKAGE_TYPE)
{
case HARD:
dh=hard_shrink(dh,SHRINKAGE_T);
dv=hard_shrink(dv,SHRINKAGE_T);
dd=hard_shrink(dd,SHRINKAGE_T);
break;
case SOFT:
dh=soft_shrink(dh,SHRINKAGE_T);
dv=soft_shrink(dv,SHRINKAGE_T);
dd=soft_shrink(dd,SHRINKAGE_T);
break;
case GARROT:
dh=Garrot_shrink(dh,SHRINKAGE_T);
dv=Garrot_shrink(dv,SHRINKAGE_T);
dd=Garrot_shrink(dd,SHRINKAGE_T);
break;
}
//-------------------
dst.at<float>(y*2,x*2)=0.5*(c+dh+dv+dd);
dst.at<float>(y*2,x*2+1)=0.5*(c-dh+dv-dd);
dst.at<float>(y*2+1,x*2)=0.5*(c+dh-dv-dd);
dst.at<float>(y*2+1,x*2+1)=0.5*(c-dh-dv+dd);
}
}
Mat C=src(Rect(0,0,width>>(k-1),height>>(k-1)));
Mat D=dst(Rect(0,0,width>>(k-1),height>>(k-1)));
D.copyTo(C);
}
}
//--------------------------------
//
//--------------------------------
int process(VideoCapture& capture)
{
int n = 0;
const int NIter=4;
char filename[200];
string window_name = "video | q or esc to quit";
cout << "press space to save a picture. q or esc to quit" << endl;
namedWindow(window_name, CV_WINDOW_KEEPRATIO); //resizable window;
Mat frame;
capture >> frame;
Mat GrayFrame=Mat(frame.rows, frame.cols, CV_8UC1);
Mat Src=Mat(frame.rows, frame.cols, CV_32FC1);
Mat Dst=Mat(frame.rows, frame.cols, CV_32FC1);
Mat Temp=Mat(frame.rows, frame.cols, CV_32FC1);
Mat Filtered=Mat(frame.rows, frame.cols, CV_32FC1);
for (;;)
{
Dst=0;
capture >> frame;
if (frame.empty()) continue;
cvtColor(frame, GrayFrame, CV_BGR2GRAY);
GrayFrame.convertTo(Src,CV_32FC1);
cvHaarWavelet(Src,Dst,NIter);
Dst.copyTo(Temp);
cvInvHaarWavelet(Temp,Filtered,NIter,GARROT,30);
imshow(window_name, frame);
double M=0,m=0;
//----------------------------------------------------
// Normalization to 0-1 range (for visualization)
//----------------------------------------------------
minMaxLoc(Dst,&m,&M);
if((M-m)>0) {Dst=Dst*(1.0/(M-m))-m/(M-m);}
imshow("Coeff", Dst);
minMaxLoc(Filtered,&m,&M);
if((M-m)>0) {Filtered=Filtered*(1.0/(M-m))-m/(M-m);}
imshow("Filtered", Filtered);
char key = (char)waitKey(5);
switch (key)
{
case 'q':
case 'Q':
case 27: //escape key
return 0;
case ' ': //Save an image
sprintf(filename,"filename%.3d.jpg",n++);
imwrite(filename,frame);
cout << "Saved " << filename << endl;
break;
default:
break;
}
}
return 0;
}
int main(int ac, char** av)
{
VideoCapture capture(0);
if (!capture.isOpened())
{
return 1;
}
return process(capture);
}
这篇关于在openCV中的小波变换的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！