opencv从入门到精通（2）--简单图像变换

1.图像滤波

这里有到两个函数cvCreateImage和 cvSmooth( image, out, CV_GAUSSIAN, 5,5,0,0 )。
cvCreateImage(cvGetSize(image),IPL_DEPTH_8U,3)用于创建
指定大小的图像，第一个参数是尺寸，第二个参数是数据类型，
第三个参数是通道数。cvSmooth( image, out, CV_GAUSSIAN, 5,5,0,0 )
用于图像滤波，第一个参数是输入图像；第二个参数是输出图像；
第三个参数是平滑方法；5,5表示5*5邻域；
第六个参数是高斯参数的 Gaussian sigma (标准差)。

#include <stdio.h>#include <fstream>#include<iostream>  #include <opencv2/core/core.hpp>  #include <opencv2/highgui/highgui.hpp>  #include "cv.h"                  using namespace cv;    using namespace std;int main( ){  IplImage* image = cvLoadImage( "a1.ppm" );//输入图像    cvNamedWindow( "Example4-in", CV_WINDOW_AUTOSIZE );//创建显示输入图像的窗口    cvNamedWindow( "Example4-out", CV_WINDOW_AUTOSIZE );//创建显示输出图像的窗口    cvShowImage( "Example4-in", image );//显示输入图像    IplImage* out = cvCreateImage(cvGetSize(image),IPL_DEPTH_8U,3);//创建和image大小相同的图像    // 平滑    cvSmooth( image, out, CV_GAUSSIAN, 5,5,0,0 );    cvSmooth( out, out, CV_GAUSSIAN, 5, 5,0,0);    cvShowImage( "Example4-out", out );    cvReleaseImage( &out );    cvWaitKey( 0 );     cvDestroyWindow("Example4-in" );    cvDestroyWindow("Example4-out" );    cvReleaseImage( &image );}

封装函数

1.图像缩放
cvPyrDown( in, out )使用Gaussian金字塔分解对输入图像向下采样。第一个参数是输入图像，第二个参数是输出图像，长宽为输入图像的一半。

#include <stdio.h>#include <fstream>#include<iostream>  #include <opencv2/core/core.hpp>  #include <opencv2/highgui/highgui.hpp>  #include "cv.h"                  using namespace cv;    using namespace std;IplImage* doPyrDown(IplImage* in,int filter = IPL_GAUSSIAN_5x5){    assert( in->width%2 == 0 && in->height%2 == 0 );//长宽不为偶数退出    IplImage* out= cvCreateImage(        cvSize( in->width/2, in->height/2 ),       in->depth,        in->nChannels    );    cvPyrDown( in, out );    return( out );};int main(  ){  IplImage* img = cvLoadImage(  "ch12_birdseye.jpg" );  IplImage* img2 = cvCreateImage( cvSize( img->width/2,img->height/2 ), img->depth, img->nChannels);  cvNamedWindow("Example1", CV_WINDOW_AUTOSIZE );  cvNamedWindow("Example2", CV_WINDOW_AUTOSIZE );  cvShowImage("Example1", img );  img2 = doPyrDown( img );  cvShowImage("Example2", img2 );  cvWaitKey(0);  cvReleaseImage( &img );  cvReleaseImage( &img2 );  cvDestroyWindow("Example1");  cvDestroyWindow("Example2");}

1. 边缘检测
   cvCvtColor(img_rgb, img_gry ,CV_BGR2GRAY)函数可以实现颜色空间的转换，第一个参数是输入图像，第二个参数是输出图像，第三个参数是转换形式——CV_BGR2GRAY表示转换为灰度图，输入需要是单通道图片；CV_BGR2HSV将图片从RGB空间转换为HSV空间，需要将rgb值归一化到0-1之间。
   函数 void cvCanny( const CvArr* image,CvArr* edges,double threshold1,double threshold2, int aperture_size=3 )采用 Canny 算法发现输入图像的边缘而且在输出图像中标识这些边缘。输入是灰度图，threshold1和threshold2 当中的小阈值用来控制边缘连接，大的阈值用来控制强边缘的初始分割， aperture_size是算子内核大小。

#include <stdio.h>#include <fstream>#include<iostream>  #include <opencv2/core/core.hpp>  #include <opencv2/highgui/highgui.hpp>  #include "cv.h"                  using namespace cv;    using namespace std;IplImage* doCanny(    IplImage* in,    double    lowThresh,    double    highThresh,    double    aperture){    if (in->nChannels != 1)        return(0);     IplImage* out = cvCreateImage(         cvGetSize( in ),        in->depth,             1);    cvCanny( in, out, lowThresh, highThresh, aperture );    return( out );};int main( ){  IplImage* img_rgb = cvLoadImage( "left01.jpg" );  IplImage* img_gry = cvCreateImage( cvSize( img_rgb->width,img_rgb->height ), img_rgb->depth, 1);  cvCvtColor(img_rgb, img_gry ,CV_BGR2GRAY);  cvNamedWindow("Example Gray", CV_WINDOW_AUTOSIZE );  cvNamedWindow("Example Canny", CV_WINDOW_AUTOSIZE );  cvShowImage("Example Gray", img_gry );  IplImage* img_cny = doCanny( img_gry, 10, 100, 3 );  cvShowImage("Example Canny", img_cny );  cvWaitKey(0);  cvReleaseImage( &img_rgb);  cvReleaseImage( &img_gry);  cvReleaseImage( &img_cny);  cvDestroyWindow("Example Gray");  cvDestroyWindow("Example Canny");}

3.嵌套使用
有了之前封装的函数，就可以很方便的对图像做一系列的变换，比如缩小两次在进行边缘检测，代码为：

#include <stdio.h>#include <fstream>#include<iostream>  #include <opencv2/core/core.hpp>  #include <opencv2/highgui/highgui.hpp>  #include "cv.h"                  using namespace cv;    using namespace std;IplImage* doCanny(    IplImage* in,    double    lowThresh,    double    highThresh,    double    aperture){    IplImage* out = cvCreateImage(         cvGetSize( in ),        in->depth, //IPL_DEPTH_8U,            1);    cvCanny( in, out, lowThresh, highThresh, aperture );    return( out );};IplImage* doPyrDown(  IplImage* in,  int       filter = IPL_GAUSSIAN_5x5){    // Best to make sure input image is divisible by two.    //    assert( in->width%2 == 0 && in->height%2 == 0 );    IplImage* out = cvCreateImage(         cvSize( in->width/2, in->height/2 ),        in->depth,        in->nChannels    );    cvPyrDown( in, out );    return( out );};int main(  ){  cvNamedWindow("Example Gray", CV_WINDOW_AUTOSIZE );  cvNamedWindow("Example Pyr", CV_WINDOW_AUTOSIZE );  cvNamedWindow("Example Canny", CV_WINDOW_AUTOSIZE );  IplImage* img_rgb = cvLoadImage("ch12_birdseye.jpg");  IplImage* out;  out = cvCreateImage( cvSize( img_rgb->width,img_rgb->height ), img_rgb->depth, 1);  cvCvtColor(img_rgb, out ,CV_BGR2GRAY);  cvShowImage("Example Gray", out );  out = doPyrDown( out );  out = doPyrDown( out );  cvShowImage("Example Pyr", out );  out = doCanny( out, 10, 100, 3 );  cvShowImage("Example Canny", out );  cvWaitKey(0);  cvReleaseImage( &out);  cvDestroyWindow("Example Gray");  cvDestroyWindow("Example Pyr");  cvDestroyWindow("Example Canny");}

对视频的每一幅图像进行变换

#include <stdio.h>#include <fstream>#include<iostream>  #include <opencv2/core/core.hpp>  #include <opencv2/highgui/highgui.hpp>  #include "cv.h"                  using namespace cv;    using namespace std;int main( ) {    cvNamedWindow( "Example2_10", CV_WINDOW_AUTOSIZE );    cvNamedWindow( "Log_Polar", CV_WINDOW_AUTOSIZE );    CvCapture* capture = cvCreateFileCapture("a2.mp4" );    if (!capture){        return -1;    }    IplImage* bgr_frame;    double fps = cvGetCaptureProperty (capture, CV_CAP_PROP_FPS);//获取帧率    printf("fps=%d\n",(int)fps);    CvSize size = cvSize(        (int)cvGetCaptureProperty( capture, CV_CAP_PROP_FRAME_WIDTH),        (int)cvGetCaptureProperty( capture, CV_CAP_PROP_FRAME_HEIGHT)    );    printf("frame (w, h) = (%d, %d)\n",size.width,size.height); CvVideoWriter* writer = cvCreateVideoWriter(          "D:\Documents\Visual Studio 2010\Projects\load and display an image\load and display an image\a3.mp4",                                      CV_FOURCC('D','X','5','0'),            fps,        size    );    IplImage* logpolar_frame = cvCreateImage(        size,        IPL_DEPTH_8U,        3    );    IplImage* gray_frame = cvCreateImage(        size,        IPL_DEPTH_8U,        1    );    while( (bgr_frame=cvQueryFrame(capture)) != NULL ) {        cvShowImage( "Example2_10", bgr_frame );        cvConvertImage(   //We never make use of this gray image            bgr_frame,            gray_frame,            CV_RGB2GRAY        );        cvLogPolar( bgr_frame, logpolar_frame,  //This is just a fun conversion the mimic's the human visual system                    cvPoint2D32f(bgr_frame->width/2,                    bgr_frame->height/2),                     40,                     CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS );        cvShowImage( "Log_Polar", logpolar_frame );        //Sigh, on linux, depending on your ffmpeg, this often won't work ...       cvWriteToAVI( writer, logpolar_frame );        char c = cvWaitKey(10);        if( c == 27 ) break;    }    cvReleaseVideoWriter( &writer );    cvReleaseImage( &gray_frame );    cvReleaseImage( &logpolar_frame );    cvReleaseCapture( &capture );    return 0;}