如何实现图像减操作

#include
#include
#include

using namespace std;
void main(unsigned char *src1, unsigned char *src2, unsigned char *dst, int width, int height)
{

IplImage *image1, *image2, *image3;
image1 = cvLoadImage("1.jpg", 0);//以灰度图像的形式读入图片 
image2 = cvLoadImage("2.jpg", 0);
cvNamedWindow("image", CV_WINDOW_AUTOSIZE);
cvNamedWindow("image2", CV_WINDOW_AUTOSIZE);
cvNamedWindow("image3", CV_WINDOW_AUTOSIZE);
cvShowImage("image", image3);
cvWaitKey(0);
int i, j;
unsigned char *p1, *p2, *p3;
p1 = src1;
p2 = src2;
p3 = dst;
for (j = 0; j< height; j++)
{
    for (i = 0; i< width; i++, p1++, p2++, p3++)
    {
        (*p3) = abs((*p1) - (*p2));
    }
}

}

1、使用opencv内置函数获取像素点灰度做差法。
bool imageSubtract(IplImage* src,IplImage* dst)
{
int row = 0;//行
int col = 0;//列
CvScalar s;

if (!src || !dst)
{
    return 0;
}
if ((src->height != dst->height) && (src->width != dst->width))
{
    return 0;
}

for (row = 0;row <src->height;row++)
{   
    for (col = 0;col<src->width;col++)
    {
        s.val[0] = fabs(cvGet2D(src,row,col).val[0]-cvGet2D(dst,row,col).val[0]); 
        cvSet2D(dst,row,col,s);//相差结果存于dst
    }
}
return 1;

}
2、使用指针获取像素灰度做差法
bool imageSubtract(IplImage* src,IplImage* dst)
{
int row = 0;//行
int col = 0;//列
uchar* pSrcData = NULL;
uchar* pDstData = NULL;
int stepSrc = 0;
int stepDst = 0;

if (!src || !dst)
{
    return 0;
}
if ((src->height != dst->height) && (src->width != dst->width))
{
    return 0;
}

pSrcData = (uchar *)src->imageData;
stepSrc = src->widthStep/sizeof(uchar);

pDstData = (uchar *)src->imageData;
stepDst = dst->widthStep/sizeof(uchar);

for (row = 0;row <src->height;row++)
{   
    for (col = 0;col<src->width;col++)
    {
        pDstData[row*stepDst+col] = abs(pSrcData[row*stepSrc+col] - pDstData[row*stepDst+col]);
    }
}
return 1;

}

忘了说明，上面两个函数都是基于单通道图像做差的。因此读入图像后要进行灰度化或者二值化才可调用。