//引入概率公式
//
#include <cstdio>
#include <cstring>
#include <iostream>
#include<cv.h>
#include<highgui.h>
#include <cmath>
#include<ctime>
using namespace std;
const int Width = 1024;
const int Height = 1024;
int Ddynamic[Width][Width];
//使用钟形曲线作为匹配概率,差值越小则匹配的概率越大,最终的要求是使匹配的概率最大,概率曲线使用matlab生成
int Probability[256] = {
255, 255, 254, 252, 250, 247, 244, 240, 235, 230, 225, 219, 213, 206, 200, 192, 185, 178, 170, 162,
155, 147, 139, 132, 124, 117, 110, 103, 96, 89, 83, 77, 71, 65, 60, 55, 50, 46, 42, 38, 35, 31, 28,
25, 23, 20, 18, 16, 14, 13, 11, 10, 9, 8, 7, 6, 5, 4, 4, 3, 3, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
};
int main()
{
clock_t start,finish;
start=clock();
IplImage * leftImage = cvLoadImage("imL1.png",0);
IplImage * rightImage = cvLoadImage("imR1.png",0);
//IplImage * leftImage = cvLoadImage("left.bmp",0);
//IplImage * rightImage = cvLoadImage("right.bmp",0);
int imageWidth = leftImage->width;
int imageHeight =leftImage->height;
IplImage * DPImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);
IplImage * effectiveImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);
IplImage * FilterImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);
unsigned char * pPixel = NULL;
unsigned char pixel;
unsigned char * pPixel2 = NULL;
unsigned char pixel2;
for (int i = 0; i< imageHeight;i++)
{
for (int j =0; j < imageWidth;j++ )
{
pPixel = (unsigned char *)DPImage->imageData + i*DPImage->widthStep + j;
*pPixel = 0;
pPixel = (unsigned char *)effectiveImage->imageData + i*effectiveImage->widthStep + j;
*pPixel = 0;
}
}
cvNamedWindow("Left",1);
cvNamedWindow("Right",1);
cvNamedWindow("Depth",1);
cvNamedWindow("effectiveImage",1);
cvShowImage("Left",leftImage);
cvShowImage("Right",rightImage);
int minD = 0;
int maxD = 31;
//假设图像是经过矫正的,那么每次都只是需要搜搜同一行的内容
int max12Diff = 5;
for (int i = 0;i < imageWidth;i++)
{
Ddynamic[0][i] = 0;
Ddynamic[i][0] = 0;
}
unsigned char * pLeftPixel = NULL;
unsigned char * pRightPixel = NULL;
unsigned char leftPixel = 0;
unsigned char rightPixel =0;
int m,n,l;
int t1 = clock();
for (int i = 0 ; i < imageHeight;i++)
{
for (int j = 0; j<imageWidth;j++)
{
for (int k = j + minD; k <= j + maxD;k++)
{
if (k <0 || k >= imageWidth)
{
}else {
pLeftPixel = (unsigned char*)leftImage->imageData + i*leftImage->widthStep + k;
pRightPixel= (unsigned char*)rightImage->imageData+i*rightImage->widthStep + j;
leftPixel = *pLeftPixel;
rightPixel = *pRightPixel;
//之前概率最大的点加上当前的概率
Ddynamic[j + 1][k + 1] = max(Ddynamic[j][k],max(Ddynamic[j][k+1],Ddynamic[j+1][k]))
+ Probability[abs(leftPixel - rightPixel)];
/* if (abs(leftPixel - rightPixel) <= max12Diff)
{
Ddynamic[j + 1][k + 1] = Ddynamic[j][k] +1;
}else if (Ddynamic[j][k+1] > Ddynamic[j+1][k])
{
Ddynamic[j + 1][k + 1] = Ddynamic[j][k+1];
}else{
Ddynamic[j+1][k+1] = Ddynamic[j+1][k];
}*/
//cout<<Ddynamic[j +1][k+1]<<" ";
}
}
//cout<<"\n";
}
//逆向搜索,找出最佳路径
m = imageWidth;
n = imageWidth;
l = Ddynamic[imageWidth][imageWidth];
while( m >= 1 && n >= 1)
{
pPixel = (unsigned char *)DPImage->imageData + i*DPImage->widthStep + m;
*pPixel = (n-m)*8;
//标记有效匹配点
pPixel = (unsigned char *)effectiveImage->imageData + i*effectiveImage->widthStep + m;
*pPixel = 255;
if (Ddynamic[m-1][n] >= Ddynamic[m][n -1] && Ddynamic[m-1][n] >= Ddynamic[m-1][n -1])
m--;
else if (Ddynamic[m][n-1] >= Ddynamic[m-1][n] && Ddynamic[m][n -1] >= Ddynamic[m-1][n -1])
n--;
else
{
//s[--l]=a[i-1];
// l -= Ddynamic[m][n];
m--;
n--;
}
}
//cvWaitKey(0);
}
//refine the depth image 7*7中值滤波
//统计未能匹配点的个数
int count = 0;
for (int i = 0 ;i< imageHeight;i++)
{
for (int j= 0; j< imageWidth;j++)
{
pPixel = (unsigned char *)effectiveImage->imageData + i*effectiveImage->widthStep + j;
pixel = *pPixel;
if (pixel == 0)
{
count++;
}
}
}
int t2 = clock();
cout<<"dt: "<<t2-t1<<endl;
cout<<"Count: "<<count<<" "<<(double)count/(imageWidth*imageHeight)<<endl;
cvShowImage("Depth",DPImage);
cvShowImage("effectiveImage",effectiveImage);
// cvWaitKey(0);
FilterImage = cvCloneImage(DPImage);
//7*7中值滤波
int halfMedianWindowSize = 3;
int medianWindowSize = 2*halfMedianWindowSize + 1;
int medianArray[100] = {0};
count = 0;
int temp = 0;
int medianVal = 0;
for (int i = halfMedianWindowSize + 1 ;i< imageHeight - halfMedianWindowSize;i++)
{
for (int j = halfMedianWindowSize; j< imageWidth - halfMedianWindowSize;j++)
{
pPixel = (unsigned char *)effectiveImage->imageData + i*effectiveImage->widthStep + j;
pixel = *pPixel;
if (pixel == 0)
{
count = 0;
for (int m = i - halfMedianWindowSize ; m <= i + halfMedianWindowSize ;m++)
{
for (int n = j - halfMedianWindowSize; n <= j + halfMedianWindowSize ;n++)
{
pPixel2 = (unsigned char *)DPImage->imageData + m*DPImage->widthStep + n;
pixel2 = *pPixel2;
if (pixel2 != 0)
{
medianArray[count] = pixel2;
count++;
}
}
//排序
for (int k = 0; k< count;k++)
{
for (int l = k + 1; l< count;l++)
{
if (medianArray[l] < medianArray[l-1] )
{