【学习opencv】医疗图像拼接，卫星图像拼接

//参考网站
// http://blog.youkuaiyun.com/xukaiwen_2016/article/details/53149794
// http://blog.youkuaiyun.com/dcrmg/article/details/52629856
//http://blog.youkuaiyun.com/czl389/article/details/60325970  (*)

方法1 

VS2010 +OpenCV2.4.9

#include "highgui/highgui.hpp"  
#include "opencv2/nonfree/nonfree.hpp"  
#include "opencv2/legacy/legacy.hpp" 

using namespace cv;

//计算原始图像点位在经过矩阵变换后在目标图像上对应位置
Point2f getTransformPoint(const Point2f originalPoint,const Mat &transformMaxtri);
static void ShowHelpText();
int main(int argc,char *argv[])  
{  
	system("color 5F");  
	ShowHelpText();
	//Mat image01=imread(argv[1]);  
	//Mat image02=imread(argv[2]);
	Mat image01,image02;  
	if (argc < 2)  
	{  
		image01 = imread("left.jpg");  
		image02 = imread("right.jpg");  
	}  
	else  
	{  
		image01 = imread(argv[1]);  
		image02 = imread(argv[2]);  
	}  
	if (image01.empty() || image02.empty())  
	{  
		return 0;//图像没有全部读取成功  
	}  
	//
	imshow("拼接图像1",image01);
	imshow("拼接图像2",image02);

	//灰度图转换
	Mat image1,image2;  
	cvtColor(image01,image1,CV_RGB2GRAY);
	cvtColor(image02,image2,CV_RGB2GRAY);

	//提取特征点  
	SiftFeatureDetector siftDetector(800);  // 海塞矩阵阈值
	vector<KeyPoint> keyPoint1,keyPoint2;  
	siftDetector.detect(image1,keyPoint1);  
	siftDetector.detect(image2,keyPoint2);	

	//特征点描述，为下边的特征点匹配做准备  
	SiftDescriptorExtractor siftDescriptor;  
	Mat imageDesc1,imageDesc2;  
	siftDescriptor.compute(image1,keyPoint1,imageDesc1);  
	siftDescriptor.compu