opencv小波变换代码

// DWT.cpp : 定义控制台应用程序的入口点。
//

#include "stdafx.h"
#include "cv.h"
#include "highgui.h"

// 二维离散小波变换（单通道浮点图像）
void DWT(IplImage *pImage, int nLayer)
{
// 执行条件
if (pImage)
{
if (pImage->nChannels == 1 &&
pImage->depth == IPL_DEPTH_32F &&
((pImage->width >> nLayer) << nLayer) == pImage->width &&
((pImage->height >> nLayer) << nLayer) == pImage->height)
{
int     i, x, y, n;
float   fValue   = 0;
float   fRadius  = sqrt(2.0f);
int     nWidth   = pImage->width;
int     nHeight  = pImage->height;
int     nHalfW   = nWidth / 2;
int     nHalfH   = nHeight / 2;
float **pData    = new float*[pImage->height];
float  *pRow     = new float[pImage->width];
float  *pColumn  = new float[pImage->height];
for (i = 0; i < pImage->height; i++)
{
pData[i] = (float*) (pImage->imageData + pImage->widthStep * i);
}
// 多层小波变换
for (n = 0; n < nLayer; n++, nWidth /= 2, nHeight /= 2, nHalfW /= 2, nHalfH /= 2)
{
// 水平变换
for (y = 0; y < nHeight; y++)
{
// 奇偶分离
memcpy(pRow, pData[y], sizeof(float) * nWidth);
for (i = 0; i < nHalfW; i++)
{
x = i * 2;
pData[y][i] = pRow[x];
pData[y][nHalfW + i] = pRow[x + 1];
}
// 提升小波变换
for (i = 0; i < nHalfW - 1; i++)
{
fValue = (pData[y][i] + pData[y][i + 1]) / 2;
pData[y][nHalfW + i] -= fValue;
}
fValue = (pData[y][nHalfW - 1] + pData[y][nHalfW - 2]) / 2;
pData[y][nWidth - 1] -= fValue;
fValue = (pData[y][nHalfW] + pData[y][nHalfW + 1]) / 4;
pData[y][0] += fValue;
for (i = 1; i < nHalfW; i++)
{
fValue = (pData[y][nHalfW + i] + pData[y][nHalfW + i - 1]) / 4;
pData[y][i] += fValue;
}
// 频带系数
for (i = 0; i < nHalfW; i++)
{
pData[y][i] *= fRadius;
pData[y][nHalfW + i] /= fRadius;
}
}
// 垂直变换
for (x = 0; x < nWidth; x++)
{
// 奇偶分离
for (i = 0; i < nHalfH; i++)
{
y = i * 2;
pColumn[i] = pData[y][x];
pColumn[nHalfH + i] = pData[y + 1][x];
}
for (i = 0; i < nHeight; i++)
{
pData[i][x] = pColumn[i];
}
// 提升小波变换
for (i = 0; i < nHalfH - 1; i++)
{
fValue = (pData[i][x] + pData[i + 1][x]) / 2;
pData[nHalfH + i][x] -= fValue;
}
fValue = (pData[nHalfH - 1][x] + pData[nHalfH - 2][x]) / 2;
pData[nHeight - 1][x] -= fValue;
fValue = (pData[nHalfH][x] + pData[nHalfH + 1][x]) / 4;
pData[0][x] += fValue;
for (i = 1; i < nHalfH; i++)
{
fValue = (pData[nHalfH + i][x] + pData[nHalfH + i - 1][x]) / 4;
pData[i][x] += fValue;
}
// 频带系数
for (i = 0; i < nHalfH; i++)
{
pData[i][x] *= fRadius;
pData[nHalfH + i][x] /= fRadius;
}
}
}
delete[] pData;
delete[] pRow;
delete[] pColumn;
}
}
}

// 二维离散小波恢复（单通道浮点图像）
//void IDWT(IplImage *pImage, int nLayer)
//{
// // 执行条件
// if (pImage)
// {
//  if (pImage->nChannels == 1 &&
//   pImage->depth == IPL_DEPTH_32F &&
//   ((pImage->width >> nLayer) << nLayer) == pImage->width &&
//   ((pImage->height >> nLayer) << nLayer) == pImage->height)
//  {
//   int     i, x, y, n;
//   float   fValue   = 0;
//   float   fRadius  = sqrt(2.0f);
//   int     nWidth   = pImage->width >> (nLayer - 1);
//   int     nHeight  = pImage->height >> (nLayer - 1);
//   int     nHalfW   = nWidth / 2;
//   int     nHalfH   = nHeight / 2;
//   float **pData    = new float*[pImage->height];
//   float  *pRow     = new float[pImage->width];
//   float  *pColumn  = new float[pImage->height];
//   for (i = 0; i < pImage->height; i++)
//   {
//    pData[i] = (float*) (pImage->imageData + pImage->widthStep * i);
//   }
//   // 多层小波恢复
//   for (n = 0; n < nLayer; n++, nWidth *= 2, nHeight *= 2, nHalfW *= 2, nHalfH *= 2)
//   {
//    // 垂直恢复
//    for (x = 0; x < nWidth; x++)
//    {
//     // 频带系数
//     for (i = 0; i < nHalfH; i++)
//     {
//      pData[i][x] /= fRadius;
//      pData[nHalfH + i][x] *= fRadius;
//     }
//     // 提升小波恢复
//     fValue = (pData[nHalfH][x] + pData[nHalfH + 1][x]) / 4;
//     pData[0][x] -= fValue;
//     for (i = 1; i < nHalfH; i++)
//     {
//      fValue = (pData[nHalfH + i][x] + pData[nHalfH + i - 1][x]) / 4;
//      pData[i][x] -= fValue;
//     }
//     for (i = 0; i < nHalfH - 1; i++)
//     {
//      fValue = (pData[i][x] + pData[i + 1][x]) / 2;
//      pData[nHalfH + i][x] += fValue;
//     }
//     fValue = (pData[nHalfH - 1][x] + pData[nHalfH - 2][x]) / 2;
//     pData[nHeight - 1][x] += fValue;
//     // 奇偶合并
//     for (i = 0; i < nHalfH; i++)
//     {
//      y = i * 2;
//      pColumn[y] = pData[i][x];
//      pColumn[y + 1] = pData[nHalfH + i][x];
//     }
//     for (i = 0; i < nHeight; i++)
//     {
//      pData[i][x] = pColumn[i];
//     }
//    }
//    // 水平恢复
//    for (y = 0; y < nHeight; y++)
//    {
//     // 频带系数
//     for (i = 0; i < nHalfW; i++)
//     {
//      pData[y][i] /= fRadius;
//      pData[y][nHalfW + i] *= fRadius;
//     }
//     // 提升小波恢复
//     fValue = (pData[y][nHalfW] + pData[y][nHalfW + 1]) / 4;
//     pData[y][0] -= fValue;
//     for (i = 1; i < nHalfW; i++)
//     {
//      fValue = (pData[y][nHalfW + i] + pData[y][nHalfW + i - 1]) / 4;
//      pData[y][i] -= fValue;
//     }
//     for (i = 0; i < nHalfW - 1; i++)
//     {
//      fValue = (pData[y][i] + pData[y][i + 1]) / 2;
//      pData[y][nHalfW + i] += fValue;
//     }
//     fValue = (pData[y][nHalfW - 1] + pData[y][nHalfW - 2]) / 2;
//     pData[y][nWidth - 1] += fValue;
//     // 奇偶合并
//     for (i = 0; i < nHalfW; i++)
//     {
//      x = i * 2;
//      pRow[x] = pData[y][i];
//      pRow[x + 1] = pData[y][nHalfW + i];
//     }
//     memcpy(pData[y], pRow, sizeof(float) * nWidth);
//    }
//   }
//   delete[] pData;
//   delete[] pRow;
//   delete[] pColumn;
//  }
// }
//}
int _tmain(int argc, _TCHAR* argv[])
{
// 小波变换层数
int nLayer = 2;
// 输入彩色图像
IplImage *pSrc = cvLoadImage("counter.jpg", 1);
// 计算小波图象大小
CvSize size = cvGetSize(pSrc);
if ((pSrc->width >> nLayer) << nLayer != pSrc->width)
{
size.width = ((pSrc->width >> nLayer) + 1) << nLayer;
}
if ((pSrc->height >> nLayer) << nLayer != pSrc->height)
{
size.height = ((pSrc->height >> nLayer) + 1) << nLayer;
}
// 创建小波图象
IplImage *pWavelet = cvCreateImage(size, IPL_DEPTH_32F, pSrc->nChannels);
if (pWavelet)
{
// 小波图象赋值
cvSetImageROI(pWavelet, cvRect(0, 0, pSrc->width, pSrc->height));
cvConvertScale(pSrc, pWavelet, 1, -128);
cvResetImageROI(pWavelet);
// 彩色图像小波变换
IplImage *pImage = cvCreateImage(cvGetSize(pWavelet), IPL_DEPTH_32F, 1);
if (pImage)
{
for (int i = 1; i <= pWavelet->nChannels; i++)
{
cvSetImageCOI(pWavelet, i);
cvCopy(pWavelet, pImage, NULL);
// 二维离散小波变换
DWT(pImage, nLayer);
// 二维离散小波恢复
// IDWT(pImage, nLayer);
cvCopy(pImage, pWavelet, NULL);
}
cvSetImageCOI(pWavelet, 0);
cvReleaseImage(&pImage);
}
// 小波变换图象
cvSetImageROI(pWavelet, cvRect(0, 0, pSrc->width, pSrc->height));
cvConvertScale(pWavelet, pSrc, 1, 128);
cvResetImageROI(pWavelet); // 本行代码有点多余，但有利用养成良好的编程习惯
cvReleaseImage(&pWavelet);
}
// 显示图像pSrc
cvNamedWindow("dwt",1);
cvShowImage("dwt",pSrc);
cvWaitKey(0);
cvDestroyWindow("dwt");

// ...
cvReleaseImage(&pSrc);

 return 0;
}