[wiki,blog]使用opencv自带的融合函数
[wiki,blog]使用opencv自带的融合函数
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#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。
