使用opencv自带的融合函数

[wiki,blog]使用opencv自带的融合函数




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   #include 
   "stdafx.h"




   #include 
   "test_precomp.hpp"




   #include 
   <opencv2/core.hpp>




   #include 
   <opencv2/highgui.hpp>









   using 
   namespace 
   cv;




   using 
   namespace 
   std;









   int 
   main()




   {




       Mat image1 = imread( 
   "c:\\3.jpg"
   );




       Mat image2 = imread( 
   "c:\\4.jpg"
   );




       ASSERT_EQ(image1.rows, image2.rows); ASSERT_EQ(image1.cols, image2.cols);









       Mat image1s, image2s;




       image1.convertTo(image1s, CV_16S);




       image2.convertTo(image2s, CV_16S);









       Mat mask1(image1s.size(), CV_8U);





   /* mask1(Rect(0, 0, mask1.cols/2, mask1.rows)).setTo(255);




       mask1(Rect(mask1.cols/2, 0, mask1.cols - mask1.cols/2, mask1.rows)).setTo(0);*/




                   mask1(Rect(0,0, mask1.cols , mask1.rows)).setTo(0);




                   mask1(Rect(0, 0, mask1.cols, mask1.rows/2)).setTo(255);














       Mat mask2(image2s.size(), CV_8U);





   /* mask2(Rect(0, 0, mask2.cols/2, mask2.rows)).setTo(0);




       mask2(Rect(mask2.cols/2, 0, mask2.cols - mask2.cols/2, mask2.rows)).setTo(255);*/




                   mask2(Rect(0,0, mask2.cols , mask2.rows)).setTo(255);




                   mask2(Rect(0, 0, mask2.cols, mask2.rows/2)).setTo(0);














       detail::MultiBandBlender blender( 
   false
   , 5);









       blender.prepare(Rect(0, 0, max(image1s.cols, image2s.cols), max(image1s.rows, image2s.rows)));




       blender.feed(image1s, mask1, Point(0,0));




       blender.feed(image2s, mask2, Point(0,0));









       Mat result_s, result_mask;




       blender.blend(result_s, result_mask);




       Mat result; result_s.convertTo(result, CV_8U);









                   cv::imshow( 
   "result"
   ,result);




                   cv::imwrite( 
   "baboon_lena.jpg"
   ,result);




                   cv::waitKey();









   }

实现了速度很快，效果很好的mulitband的结果，但是对于实际的项目也是有不足的，就是只能输入两幅图像。如果需要用于实际的项目，就需要进行修正，使得其能够一下子用于许多图像。