opencv图像全景拼接

网上搜的都是一行代码Stitcher::Status status = stitcher.stitch(imgs, pano);就出来的傻瓜拼接，连OpenCV基本的包都没用。

自己好歹用了下基本的包实现了下。

鲁棒性不太好，图片少的时候没事，图片一多就出现了内存错误和木有特征点的错误。

#include <iostream>
#include <fstream>
#include <io.h>
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/stitching/stitcher.hpp"
#include "opencv2/stitching/warpers.hpp"

#define MaxPics 30
//F:\Program Files\opencv\modules\stitching\include\opencv2\stitching
using namespace std;
using namespace cv;
bool try_use_gpu = false;
int filenum;
vector<Mat> imgs;
string result_name = "result.jpg";
//void printUsage();
//int parseCmdArgs(int argc, char** argv);
int readDir(char *path,char fnames[MaxPics][100]);

int readDir(char *path,char fnames[MaxPics][100]) 
{ 
struct _finddata_t c_file;
intptr_t hFile;
filenum=0;

char fullpath[100];

sprintf(fullpath,"%s\\*.jpg",path);
// Find first .c file in current directory 
if( (hFile = _findfirst( fullpath, &c_file )) == -1L )
printf( "No *.jpg files in current directory %s!\n",fullpath);
else
{
printf( "Listing of .jpg files in %s directory\n\n",path);
printf( "RDO HID SYS ARC FILE SIZE\n", ' ' );
printf( "--- --- --- --- ---- ----\n", ' ' );
do {
printf( ( c_file.attrib & _A_RDONLY ) ? " Y " : " N " );
printf( ( c_file.attrib & _A_SYSTEM ) ? " Y " : " N " );
printf( ( c_file.attrib & _A_HIDDEN ) ? " Y " : " N " );
printf( ( c_file.attrib & _A_ARCH ) ? " Y " : " N " );
//ctime_s( buffer, _countof(buffer), &c_file.time_write );
printf( " %-15s %9ld\n",c_file.name, c_file.size );
sprintf(fnames[filenum],"%s\\%s",path,c_file.name);
filenum++;
} while( _findnext( hFile, &c_file ) == 0 );
_findclose( hFile );
}
return filenum;
} 
int main(int argc, char* argv[])
{
clock_t start,finish;
double totaltime;
start=clock();

argv[1]="pic";
char fdir[MaxPics][100];
filenum = readDir(argv[1],fdir);
Mat img, pano;
for(int i=0 ; i<filenum ;i++){
img = imread(fdir[i]);
imgs.push_back(img);
}
Stitcher stitcher = Stitcher::createDefault(try_use_gpu);
stitcher.setRegistrationResol(0.1);//为了加速，我选0.1,默认是0.6,最大值1最慢，此方法用于特征点检测阶段，如果找不到特征点，调高吧
//stitcher.setSeamEstimationResol(0.1);//默认是0.1
//stitcher.setCompositingResol(-1);//默认是-1，用于特征点检测阶段，找不到特征点的话，改-1
stitcher.setPanoConfidenceThresh(1);//默认是1,见过有设0.6和0.4的
stitcher.setWaveCorrection(false);//默认是true，为加速选false，表示跳过WaveCorrection步骤
//stitcher.setWaveCorrectKind(detail::WAVE_CORRECT_HORIZ);//还可以选detail::WAVE_CORRECT_VERT ,波段修正(wave correction)功能（水平方向/垂直方向修正）。因为setWaveCorrection设的false，此语句没用

//找特征点surf算法，此算法计算量大,但对刚体运动、缩放、环境影响等情况下较为稳定
detail::SurfFeaturesFinder *featureFinder = new detail::SurfFeaturesFinder();
stitcher.setFeaturesFinder(featureFinder);

//找特征点ORB算法,但是发现草地这组图，这个算法不能完成拼接
//detail::OrbFeaturesFinder *featureFinder = new detail::OrbFeaturesFinder();
//stitcher.setFeaturesFinder(featureFinder);

//Features matcher which finds two best matches for each feature and leaves the best one only if the ratio between descriptor distances is greater than the threshold match_conf.
detail::BestOf2NearestMatcher *matcher = new detail::BestOf2NearestMatcher(false, 0.5f/*=match_conf默认是0.65，我选0.8，选太大了就没特征点啦,0.8都失败了*/);
stitcher.setFeaturesMatcher(matcher);

// Rotation Estimation,It takes features of all images, pairwise matches between all images and estimates rotations of all cameras.
//Implementation of the camera parameters refinement algorithm which minimizes sum of the distances between the rays passing through the camera center and a feature,这个耗时短
stitcher.setBundleAdjuster(new detail::BundleAdjusterRay());
//Implementation of the camera parameters refinement algorithm which minimizes sum of the reprojection error squares.
//stitcher.setBundleAdjuster(new detail::BundleAdjusterReproj());

//Seam Estimation
//Minimum graph cut-based seam estimator
//stitcher.setSeamFinder(new detail::GraphCutSeamFinder(detail::GraphCutSeamFinderBase::COST_COLOR));//默认就是这个
//stitcher.setSeamFinder(new detail::GraphCutSeamFinder(detail::GraphCutSeamFinderBase::COST_COLOR_GRAD));//GraphCutSeamFinder的第二种形式
//啥SeamFinder也不用，Stub seam estimator which does nothing.
stitcher.setSeamFinder(new detail::NoSeamFinder);
//Voronoi diagram-based seam estimator.
//stitcher.setSeamFinder(new detail::VoronoiSeamFinder);

//exposure compensators曝光补偿
//stitcher.setExposureCompensator(new detail::BlocksGainCompensator());//默认的就是这个
//不要曝光补偿
stitcher.setExposureCompensator(new detail::NoExposureCompensator());
//Exposure compensator which tries to remove exposure related artifacts by adjusting image intensities
//stitcher.setExposureCompensator(new detail::detail::GainCompensator());
//Exposure compensator which tries to remove exposure related artifacts by adjusting image block intensities 
//stitcher.setExposureCompensator(new detail::detail::BlocksGainCompensator()); 

//Image Blenders
//Blender which uses multi-band blending algorithm 
//stitcher.setBlender(new detail::MultiBandBlender(try_use_gpu));//默认的是这个
//Simple blender which mixes images at its borders
stitcher.setBlender(new detail::FeatherBlender());//这个简单，耗时少

//柱面？球面OR平面？默认为球面
PlaneWarper* cw = new PlaneWarper();
//SphericalWarper* cw = new SphericalWarper();
//CylindricalWarper* cw = new CylindricalWarper();
stitcher.setWarper(cw);

Stitcher::Status status = stitcher.estimateTransform(imgs);
if (status != Stitcher::OK)
{
cout << "Can't stitch images, error code = " << int(status) << endl;
return -1;
}
status = stitcher.composePanorama(pano);
if (status != Stitcher::OK)
{
cout << "Can't stitch images, error code = " << int(status) << endl;
return -1;
}
cout<<"程序开始";
imwrite(result_name, pano);
finish=clock();
totaltime=(double)(finish-start)/CLOCKS_PER_SEC;
cout<<"\n此程序的运行时间为"<<totaltime<<"秒！"<<endl;
return 0;
}

至于其他的拼接方式，http://academy.nearsoft.com/project-updates/makingapanoramapicture写的挺好。我引用之，并总结如下

1，Stitcher class from OpenCV library

• Pros
  • Extremely simple. Build panorama in just one command.
  • It performs from finding features through blending in the selected projection by itself.
• Cons
  • Uses SURF algorithm (patented, not allowed for commercial use).
  • Slow at searching for features, running on a smartphone

2，BoofCV 

• Pros
  • Still easy to use.
  • Java native.
• Cons
  • It blends without warping into the spherical projection.
  • Still uses SURF.

当然自己实现最好，我的上述代码就是第一种了

转：http://blog.youkuaiyun.com/manji_lee/article/details/9002228