满意答案

#include "stdafx.h"

#include

#include

#include

#include

#include

#include

using namespace std;

const int Width = 1024;

const int Height = 1024;

int Lvalue[Width][Width];

uchar C(int x, int y, int d, IplImage * matchImage, IplImage * baseImage)

{

uchar * pMatchPixel = NULL;

uchar * pBasePixel = NULL;

uchar matchPixel = 0;

uchar basePixel =0;

uchar matchMax = 0;

uchar matchMin = 0;

uchar tempMatch1 = 0;

uchar tempMatch2 = 0;

uchar difPixel = 0;

if (x+d <= matchImage->width && x+d >= 0)

{

pMatchPixel = (uchar *)matchImage->imageData + y*matchImage->widthStep + (x+d);

matchPixel = *pMatchPixel;

pBasePixel= (uchar *)baseImage->imageData + y*baseImage->widthStep + x;

basePixel = *pBasePixel;

//匹配影像上的像素点与其左、右像素点的平均值,线性插值的方法

tempMatch1 = (*pMatchPixel +(*(pMatchPixel -1)))/2;

tempMatch2 = (*pMatchPixel +(*(pMatchPixel +1)))/2;

matchMax = max(max(tempMatch1,tempMatch2),matchPixel);

matchMin = min(min(tempMatch1,tempMatch2),matchPixel);

//赋予视差d时的匹配代价C

//BT法

difPixel = max(max(basePixel - matchMax, matchMin - basePixel),0);

//AD法

//difPixel = abs(basePixel - matchPixel);

return difPixel;

}

else

return 255;

}

int main()

{

IplImage * leftImage = cvLoadImage("headL.png",0);

IplImage * rightImage = cvLoadImage("headR.png",0);

int imageWidth = leftImage->width;

int imageHeight =leftImage->height;

int minLvalue = 1000;

int minL1 = 1000;

int minL2 = 1000;

int P1 = 2;

int P2 = 5;

int disparity= 0;

int minDis = 0;

int maxDis = 21;

int scale = 12;

unsigned char * pPixel = NULL;

#pragma region 实现横向DP(以右影像为准,0度方向)

IplImage * MyDPImage_0 = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);

cvZero(MyDPImage_0);

int t3 = clock();

for (int i = 0; i < imageHeight;i++)

{

for (int j = 0; j

{

disparity = 0;

minL1 = 1000;

minL2 = 1000;

for (int d = minDis; d <= maxDis; d++)

{

//初始化为代价函数的值

Lvalue[j][d] = C(j, i, d, leftImage, rightImage);

if (j > 0)

{

minL1 = min(minL1, Lvalue[j-1][d]);

}

}

for (int d = minDis; d <= maxDis; d++)

{

if (j > 0)

{

minL2 = min(minL2, Lvalue[j-1][d]);

minL2 = min(minL2, (Lvalue[j-1][d+1] + P1));

minL2 = min(minL2, (Lvalue[j-1][d-1] + P1));

minL2 = min(minL2, (minL1 + P2));

Lvalue[j][d] = Lvalue[j][d] + (minL2 - minL1);

}

}

int max=Lvalue[j][0];

for(int d=minDis;d<=maxDis;++d)

{

if(Lvalue[j][d]

{

disparity=d;

max=Lvalue[j][d];

}

}

disparity=disparity*scale;

//生成视差图

pPixel = (uchar *)MyDPImage_0->imageData + i*MyDPImage_0->widthStep + j;

*pPixel =disparity;

}

}

int t4 = clock();

cout<

cvNamedWindow("MyDPImage_0", 1);

cvShowImage("MyDPImage_0", MyDPImage_0);

cvSaveImage("MyDPImage_0.jpg", MyDPImage_0);

#pragma endregion

#pragma region 实现横向DP(以左影像为准，0度方向)

IplImage * MyDPImage_0_L = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);

cvZero(MyDPImage_0_L);

for (int i = 0; i < imageHeight;i++)

{

for (int j = 0; j

{

disparity = 0;

minL1 = 1000;

minL2 = 1000;

for (int d = minDis; d <= maxDis; d++)

{

//初始化为代价函数的值

Lvalue[j][d] = C(j, i, -d, rightImage, leftImage);

if (j > 0)

{

minL1 = min(minL1, Lvalue[j-1][d]);

}

}

for (int d = minDis; d <= maxDis; d++)

{

if (j > 0)

{

minL2 = min(minL2, Lvalue[j-1][d]);

minL2 = min(minL2, (Lvalue[j-1][d+1] + P1));

minL2 = min(minL2, (Lvalue[j-1][d-1] + P1));

minL2 = min(minL2, (minL1 + P2));

Lvalue[j][d] = Lvalue[j][d] + minL2 - minL1;

}

}

int max=Lvalue[j][0];

for(int d=0;d<=maxDis;++d)

{

if(Lvalue[j][d]

{

disparity=d;

max=Lvalue[j][d];

}

}

disparity = disparity * scale;

//生成视差图

pPixel = (uchar *)MyDPImage_0_L->imageData + i*MyDPImage_0_L->widthStep + j;

*pPixel = disparity;

}

}

cvNamedWindow("MyDPImage_0_L", 1);

cvShowImage("MyDPImage_0_L", MyDPImage_0_L);

cvSaveImage("MyDPImage_0_L.jpg", MyDPImage_0_L);

#pragma endregion

#pragma region 一致性检查

uchar * pLeftDepthPixel = NULL;

uchar * pRightDepthPixel = NULL;

uchar leftDepthPixel = 0;

uchar rightDepthPixel =0;

uchar difDepthPixel = 0;

IplImage * CheckImage_0 = cvCloneImage(MyDPImage_0);

cvZero(CheckImage_0);

for (int i = 0; i < imageHeight; i++)

{

for(int j = 0; j < imageWidth; j++)

{

pRightDepthPixel = (uchar *)MyDPImage_0->imageData + i*MyDPImage_0->widthStep + j;

rightDepthPixel = *pRightDepthPixel;

if(j + rightDepthPixel/scale < imageWidth)

{

pLeftDepthPixel = (uchar *)MyDPImage_0_L->imageData + i*MyDPImage_0_L->widthStep + j + rightDepthPixel/scale;

leftDepthPixel = *pLeftDepthPixel;

}

else

leftDepthPixel = 0;

difDepthPixel = abs((leftDepthPixel - rightDepthPixel)/scale);

pPixel = (uchar *)CheckImage_0->imageData + i * CheckImage_0->widthStep +j;

if (difDepthPixel <= 1)

{

*pPixel = rightDepthPixel;

}

else

{

//否则，当前像素的视差值为零

*pPixel = 0;

}

}

}

int lp,rp;

int lx,rx;

for(int i=0;i

{

for(int j=0;j

{

int tem = *((uchar *)CheckImage_0->imageData+i*CheckImage_0->widthStep + j);

if(tem==0)

{

lp = rp = 0;

lx = j;

rx = j;

if(lx-1<0)

lp= *((uchar *)CheckImage_0->imageData+i*CheckImage_0->widthStep + lx);

while((lp==0)&&( lx-1 >= 0 ))

lp = *((uchar *)CheckImage_0->imageData+i*CheckImage_0->widthStep + (--lx));

if(rx+1>=imageWidth)

rp = *((uchar *)CheckImage_0->imageData+i*CheckImage_0->widthStep + rx);

while((rp==0)&&(rx+1

rp = *((uchar *)CheckImage_0->imageData+i*CheckImage_0->widthStep +(++rx));

if (lp > rp)

{

*((uchar *)CheckImage_0->imageData+i*CheckImage_0->widthStep + j) = rp;

}

else

{

*((uchar *)CheckImage_0->imageData+i*CheckImage_0->widthStep + j) = lp;

}

}

}

}

cvSmooth(CheckImage_0,CheckImage_0,CV_MEDIAN,3,0,0);

cvNamedWindow("CheckImage_0", 1);

cvShowImage("CheckImage_0", CheckImage_0);

cvSaveImage("CheckImage_0.jpg", CheckImage_0);

#pragma endregion

cout << "完成！"<

cvWaitKey(0);

return 0;

}

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