//优化两图的连接处，使得拼接自然
void OptimizeSeam(Mat& img1, Mat& trans, Mat& dst)
{	
	int start = MIN(corners.left_top.x, corners.left_bottom.x);//开始位置，即重叠区域的左边界   	
	double processWidth = img1.cols - start;//重叠区域的宽度  	
	int rows = dst.rows;	
	int cols = img1.cols; //注意，是列数*通道数	
	double alpha = 1;//img1中像素的权重  	
	for (int i = 0; i < rows; i++)	
	{		
		uchar* p = img1.ptr<uchar>(i);  //获取第i行的首地址		
		uchar* t = trans.ptr<uchar>(i);		
		uchar* d = dst.ptr<uchar>(i);		
		for (int j = start; j < cols; j++)		
		{		
			//如果遇到图像trans中无像素的黑点，则完全拷贝img1中的数据		
			if (t[j * 3] == 0 && t[j * 3 + 1] == 0 && t[j * 3 + 2] == 0)			{	
			alpha = 1;			}		
			else			{			
			//img1中像素的权重，与当前处理点距重叠区域左边界的距离成正比，实验证明，这种方法确实好  	
			alpha = (processWidth - (j - start)) / processWidth;			} 		
			d[j * 3] = p[j * 3] * alpha + t[j * 3] * (1 - alpha);	
			d[j * 3 + 1] = p[j * 3 + 1] * alpha + t[j * 3 + 1] * (1 - alpha);	
			d[j * 3 + 2] = p[j * 3 + 2] * alpha + t[j * 3 + 2] * (1 - alpha); 	
	    }	
			
	} 
}