图像处理之图像拼接四

1 亮度校正的代码

实际上就是把图像im1 和图像im2 的重合部分转换到hsv颜色空间中，计算两个重合部分亮度和的比值，用这个比值去校正图像im2

void colorjust(cv::Mat &im1,cv::Mat &im2, int stitchlength)
{
int soureheight=im1.rows;
int sourewidth=im1.cols;
int xsum=stitchlength;
/////////////////////////////////////////
int channle = im1.channels();
float v2=0;
for (int jx=0;jx<soureheight;jx++)
{
uchar *data =im2.ptr<uchar>(jx);
for (int iy=0;iy<xsum;iy++)
{
float I2=0.59*data[iy*channle+0]+0.11*data[iy*channle+1]+0.3*data[iy*channle+2];
v2=v2+I2;
}
}

float v1=0;
for (int jx=0;jx<soureheight;jx++)
{
uchar *data =im1.ptr<uchar>(jx);
for (int iy=sourewidth-xsum;iy<sourewidth;iy++)
{
float I1=0.59*data[iy*channle+0]+0.11*data[iy*channle+1]+0.3*data[iy*channle+2];
v1=v1+I1;
}
}
float k=v1/v2;
for (int jx=0;jx<soureheight;jx++)
{
uchar *data =im2.ptr<uchar>(jx);
for (int iy=0;iy<sourewidth;iy++)
{
data[iy*channle+0]=k*data[iy*channle+0];
data[iy*channle+1]=k*data[iy*channle+1];
data[iy*channle+2]=k*data[iy*channle+2];
}
}
}

2 弄出背景，转到lab空间，分离处L，根据这个L建立一个模板，求解L到L模板的映射。来一个图像，将这个图像分离处L，利用映射去校正，然后回到RGB空间中

void newbackground(IplImage *image1, cv::Mat& listtable)
{

//读取背景图像，分离出l分量放入testimg
IplImage *testimg=cvCreateImage(cvGetSize(image1),8,1);
IplImage *newtestimg=cvCreateImage(cvGetSize(image1),8,1);
cvZero(testimg);
cvZero(newtestimg);
cv::Mat ming1(image1,0);
cv::cvtColor(ming1, ming1, CV_BGR2Lab);
uchar *data1;
int channle = ming1.channels();
for(int x=0;x<image1->height;x++)
{
data1 =ming1.ptr<uchar>(x);
for(int y=0;y<image1->width;y++)
{
BYTE vb=ming1.at<cv::Vec3b>(x,y)[0];
BYTE vg=ming1.at<cv::Vec3b>(x,y)[1];
BYTE vr=ming1.at<cv::Vec3b>(x,y)[2];
float vm11=vb;
cvSet2D(testimg,x,y,cvScalar(vm11));

}
}
//背景建模
int time=4;
cv::Mat mingt(testimg,0);
cv::Mat mingnt(newtestimg,0);
uchar *datan=mingt.ptr<uchar>(testimg->height/2);
int centervalue=datan[testimg->width/2];
for (int i=1;i<=time;i++)
{
if (i==1)
{
for(int x=0;x<testimg->height;x++)
{
uchar *datant=mingnt.ptr<uchar>(x);
for(int y=0;y<testimg->width;y++)
{
datant[y]=centervalue-3;
}
}
}else if (i==2)
{
for(int x=testimg->height/4;x<testimg->height*0.75;x++)
{
uchar *datant=mingnt.ptr<uchar>(x);
for(int y=testimg->width/4;y<testimg->width*0.75;y++)
{
datant[y]=centervalue-2;
}
}
}else if (i==3)
{
for(int x=3*testimg->height/8;x<5*testimg->height/8;x++)
{
uchar *datant=mingnt.ptr<uchar>(x);
for(int y=3*testimg->width/8;y<5*testimg->width/8;y++)
{
datant[y]=centervalue-1;
}
}
}else if (i==4)
{
for(int x=7*testimg->height/16;x<9*testimg->height/16;x++)
{
uchar *datant=mingnt.ptr<uchar>(x);
for(int y=7*testimg->width/16;y<9*testimg->width/16;y++)
{
datant[y]=centervalue;
}
}
}
}
//计算list
for(int x=0;x<testimg->height;x++)
{
uchar *datat=mingt.ptr<uchar>(x);
uchar *datant=mingnt.ptr<uchar>(x);
for(int y=0;y<testimg->width;y++)
{
if (datat[y]!=0)
{
float value=(float)datant[y]/(float)datat[y];
listtable.ptr<float>(x)[y]=value;
}

}
}
//释放
cvReleaseImage(&testimg);
cvReleaseImage(&newtestimg);

}