图像旋转的MATLAB和OpenCV源码!

ゝ一纸荒年。 2022-07-24 11:10 229阅读 0赞

图像旋转的意义就不多说了，直接上源码吧！

源码中用到的lena.jpg、lena\_gray.png、pool.jpg图像的下载链接分别为：

[http://pan.baidu.com/s/1sl1jEKt][http_pan.baidu.com_s_1sl1jEKt]

[http://pan.baidu.com/s/1bo5zC2F][http_pan.baidu.com_s_1bo5zC2F]  
[http://pan.baidu.com/s/1dFv2MM9][http_pan.baidu.com_s_1dFv2MM9]

先要说明的是，MATLAB得出的图像和OpenCV得出的源码在数据上是有差别的，但是都是对的！

先上MATLAB处理灰度图像的源码：

clear all;
    close all;
    clc;
    a=imread('lena.jpg');
    a=rgb2gray(a);
    a1=imrotate(a,30,'bilinear');%%旋转函数，30为旋转角度，bilinear为旋转后不是整数点的像素值 通过双线性插值得到。当旋转角度为正时，逆时针旋转；当旋转角度为负时，顺时针旋转。
    figure,imshow(a);
    figure,imshow(a1);

再上MATLAB处理彩色图像的源码：

clear all;
    close all;
    clc;
    a=imread('lena.jpg');
    
    R=a(:,:,1);
    G=a(:,:,2);
    B=a(:,:,3);
    
    R_r=imrotate(R,30,'bilinear');%旋转函数，30为旋转角度，bilinear为旋转后不是整数点的像素值 通过双线性插值得到。当旋转角度为正时，逆时针旋转；当旋转角度为负时，顺时针旋转。
    G_r=imrotate(G,30,'bilinear');
    B_r=imrotate(B,30,'bilinear');
    
    a1(:,:,1)=R_r;
    a1(:,:,2)=G_r;
    a1(:,:,3)=B_r;
    
    figure,imshow(a);
    figure,imshow(a1);

再上OpenCV处理灰度级图像旋转的C源码(不使用MAT类)：

#include <opencv2/opencv.hpp>  
    #include <opencv2/legacy/compat.hpp> 
    #include <fstream>
    using namespace std;  
    #pragma comment(linker, "/subsystem:\"windows\" /entry:\"mainCRTStartup\"")  
    
    
    IplImage *FitRotate (IplImage* Img_old, double angle,int method) //使用透视变换实现图像的旋转
    
    {
    
    	IplImage* Img_tmp = NULL; 
    
    	double anglerad  = (CV_PI* (angle/180)) ;//把角度制化为弧度制
    	//计算旋转之后图片的新高度和宽度
    	int newheight =int (fabs(( sin(anglerad)*Img_old->width )) + fabs(( cos(anglerad)*Img_old->height )) );
    	int newwidth  =int (fabs(( sin(anglerad)*Img_old->height)) + fabs(( cos(anglerad)*Img_old->width)) );
    	     
    	Img_tmp = cvCreateImage(cvSize(newwidth,newheight), IPL_DEPTH_8U, 1);
    	cvFillImage(Img_tmp,0);//如果return Img_tmp;则旋转后的图像与输入图像大小不一致
    
    	IplImage* dst = cvCloneImage( Img_old );//如果return dst;则旋转后的图像与输入图像大小一致
    
    	     
    	float m[6];            
    	CvMat M = cvMat( 2, 3, CV_32F, m );
    
    	//从这里开始是核心算法
    
    	  CvPoint2D32f src_point[4];
          CvPoint2D32f dst_point[4];
    
          src_point[0].x=0.0;                    src_point[0].y=0.0;
          src_point[1].x=0.0;                    src_point[1].y=(float) Img_old->height; 
          src_point[2].x=(float) Img_old->width; src_point[2].y=(float) Img_old->height;
          src_point[3].x=(float) Img_old->width; src_point[3].y=0.0;
    
    
          dst_point[0].x=0;               
          dst_point[0].y=(float) fabs(( sin(anglerad)*Img_old->width ));
    
          dst_point[1].x=(float) fabs(( sin(anglerad)*Img_old->height));              
          dst_point[1].y=(float) fabs(( sin(anglerad)*Img_old->width ))+(float) fabs(( cos(anglerad)*Img_old->height));
        
          dst_point[2].x=(float) fabs(( sin(anglerad)*Img_old->height))+(float) fabs(( cos(anglerad)*Img_old->width));
          dst_point[2].y=(float) fabs(( cos(anglerad)*Img_old->height));
    
          dst_point[3].x=(float) fabs(( cos(anglerad)*Img_old->width));
          dst_point[3].y=0;
        
           
          float newm[9];            
          CvMat newM = cvMat( 3, 3, CV_32F, newm );
          cvWarpPerspectiveQMatrix(src_point,dst_point,&newM);
       
          cvWarpPerspective(Img_old,dst,&newM,CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS, cvScalarAll(0) );
          cvWarpPerspective(Img_old,Img_tmp,&newM,CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS, cvScalarAll(0) );
    
       
         return Img_tmp;
    	 //return dst;
    
        }
    
    int main()
    {
    
    	IplImage *pSrcImage = cvLoadImage("lena.png", CV_LOAD_IMAGE_UNCHANGED);  
    	//IplImage *pOutImage = cvCreateImage(cvGetSize(pSrcImage), IPL_DEPTH_8U,1);
    	IplImage *pOutImage = NULL;
    
    	pOutImage=FitRotate(pSrcImage,70,1);
    
    	cvSaveImage("pOutImage_lena.png",pOutImage);  
    
    	const char *pstrWindowsATitle = "原图";  
    	const char *pstrWindowsBTitle = "变换后的图"; 
    	//创建窗口      
    	cvNamedWindow(pstrWindowsATitle, CV_WINDOW_AUTOSIZE);      
    	cvNamedWindow(pstrWindowsBTitle, CV_WINDOW_AUTOSIZE);
    	//在指定窗口中显示图像      
    	cvShowImage(pstrWindowsATitle, pSrcImage);    
    	cvShowImage(pstrWindowsBTitle, pOutImage);    
    	//等待按键事件      
    	cvWaitKey();      
    	cvDestroyWindow(pstrWindowsATitle);  
    	cvDestroyWindow(pstrWindowsBTitle); 
    	cvReleaseImage(&pSrcImage);  
    	cvReleaseImage(&pOutImage);    
    
    return 0;
    }

再上OpenCV处理RGB图像旋转的C源码(不使用MAT类)：

#include <opencv2/opencv.hpp>  
    #include <opencv2/legacy/compat.hpp> 
    #include <fstream>
    using namespace std;  
    #pragma comment(linker, "/subsystem:\"windows\" /entry:\"mainCRTStartup\"")  
    
    
    int main()  
    {  
        double degree = 30; // rotate 30 degree  
        double angle = degree  * CV_PI / 180.; // angle in radian  
        double a = sin(angle), b = cos(angle); // sine and cosine of angle  
      
        // Load source image as you wish  
        IplImage *imgSrc = cvLoadImage("lena.jpg");  
        int w_src = imgSrc->width;  
        int h_src = imgSrc->height;  
        cvNamedWindow ("src", 1);  
        cvShowImage ("src", imgSrc);  
        // Make w_dst and h_dst to fit the output image  
        int w_dst = int(h_src * fabs(a) + w_src * fabs(b));  
        int h_dst = int(w_src * fabs(a) + h_src * fabs(b));  
      
        // map matrix for WarpAffine, stored in statck array  
        double map[6];  
        CvMat map_matrix = cvMat(2, 3, CV_64FC1, map);  
      
        // Rotation center needed for cv2DRotationMatrix  
        CvPoint2D32f pt = cvPoint2D32f(w_src / 2, h_src / 2);  
        cv2DRotationMatrix(pt, degree, 1.0, &map_matrix);  
      
        // Adjust rotation center to dst's center,  
        // otherwise you will get only part of the result  
        map[2] += (w_dst - w_src) / 2;  
        map[5] += (h_dst - h_src) / 2;  
      
      
        // We need a destination image  
      
        IplImage *imgDst = cvCreateImage(cvSize(w_dst, h_dst), 8, 3); //按我的想像,如果把3改成1就能处理灰度图像才对,但要报错
        cvWarpAffine(  
            imgSrc,   
            imgDst,  
            &map_matrix,  
            CV_INTER_LINEAR | CV_WARP_FILL_OUTLIERS,  
            cvScalarAll(0)  
            );  
    
    	//cvSaveImage("lena_gray_rotation.png",imgDst);  //将图像保存到硬盘
      
        // Don't forget to release imgSrc and imgDst if you no longer need them  
        cvNamedWindow( "dst_big", 1 );  
        cvShowImage( "dst_big", imgDst);  
      
        cvWaitKey(0);  
        cvReleaseImage(&imgSrc);  
        cvReleaseImage(&imgDst);  
        return 0;  
    }

需要说明的是，按理在OpenCV处理RGB图像旋转的源码中，把语句 IplImage \*imgDst = cvCreateImage(cvSize(w\_dst, h\_dst), 8, 3); 中的3改成1，应该就可以处理灰度图像才对，但我试了，报错，不知道怎么回事！我的源图像是灰度图像也报错！

结果如下图所示：

MATLAB的结果：

![20160521102812782][]

![20160521102820665][]

OpenCV的结果：

![20160521102828431][]

![20160521102825000][]

再上OpenCV的C++源码(使用MAT类,并且RGB和灰度图像都能处理)

//OpenCV版本2.4.9  
    //交流QQ2487872782 
    
    
    #include <opencv2/core/core.hpp>        
    #include <opencv2/highgui/highgui.hpp> 
    #include <opencv2/imgproc/imgproc.hpp>  
    #include <iostream>
    #include <cmath>
    using namespace cv;
    using namespace std;
    cv::Mat angelRotate(cv::Mat& src, int angle)
    {
        // 角度转换
        float alpha = float(angle * CV_PI / 180);
        // 构造旋转矩阵
        float rotateMat[3][3] = { 
            {cos(alpha), -sin(alpha), 0},
            {sin(alpha), cos(alpha), 0}, 
            {0, 0, 1} };
        int nSrcRows = src.rows;
        int nSrcCols = src.cols;
        // 计算旋转后图像矩阵各个顶点位置
        float a1 = nSrcCols * rotateMat[0][0] ;
        float b1 = nSrcCols * rotateMat[1][0] ;
        float a2 = nSrcCols * rotateMat[0][0] + 
            nSrcRows * rotateMat[0][1];
        float b2 = nSrcCols * rotateMat[1][0] +
            nSrcRows * rotateMat[1][1];
        float a3 = nSrcRows * rotateMat[0][1];
        float b3 = nSrcRows * rotateMat[1][1];
        // 计算出极值点
        float kxMin =  min( min( min(0.0f,a1), a2 ), a3);
        float kxMax =  max( max( max(0.0f,a1), a2 ), a3);
        float kyMin =  min( min( min(0.0f,b1), b2 ), b3);
        float kyMax =  max( max( max(0.0f,b1), b2 ), b3);
        // 计算输出矩阵的尺寸
        int nRows = int(abs(kxMax - kxMin));
        int nCols = int(abs(kyMax - kyMin));
        cv::Mat dst(nRows, nCols, src.type(),cv::Scalar::all(0)); 
        for( int i = 0; i < nRows; ++i)
        {       
            for (int  j = 0; j < nCols; ++j)
            {
                // 旋转坐标转换
                int x =  (j + kxMin) * rotateMat[0][0] -
                    (i + kyMin) * rotateMat[0][1] ;
                int y = -(j + kxMin) * rotateMat[1][0] + 
                    (i + kyMin) * rotateMat[1][1] ;
                if( (x >= 0) && (x < nSrcCols) && 
                    (y >= 0) && (y < nSrcRows) ) 
                {  
                    dst.at<cv::Vec3b>(i,j) = 
                        src.at<cv::Vec3b>(y,x);
                }
            }
        }
        return dst;
    }
    int main()
    {
        /*cv::Mat srcImage = cv::imread("pool.jpg"); */
    	cv::Mat srcImage = cv::imread("lena_gray.png"); 
        if(!srcImage.data) 
            return -1;
        cv::imshow("srcImage", srcImage); 
        int angle = 30;
        cv::Mat resultImage = angelRotate(srcImage, angle);
        imshow("resultImage", resultImage);
        cv::waitKey(0);
        return 0;
    }

运行结果如下图所示：

![20160527151249674][]![20160527151253721][]

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图像处理开发资料、图像处理开发需求、图像处理接私活挣零花钱，可以搜索公众号"qxsf321"，并关注！  
图像处理开发资料、图像处理开发需求、图像处理接私活挣零花钱，可以搜索公众号"qxsf321"，并关注！

[http_pan.baidu.com_s_1sl1jEKt]: http://pan.baidu.com/s/1sl1jEKt
[http_pan.baidu.com_s_1bo5zC2F]: http://pan.baidu.com/s/1bo5zC2F/
[http_pan.baidu.com_s_1dFv2MM9]: http://pan.baidu.com/s/1dFv2MM9
[20160521102812782]: /images/20220722/2fe97087573b46c9b7875250a363a86e.png
[20160521102820665]: /images/20220722/b8b58710e3974aca89323d5f95727ded.png
[20160521102828431]: /images/20220722/6caf97c0432d4290b355c96902cb2ac4.png
[20160521102825000]: /images/20220722/4588c896f002453fabd2e08a65ad6305.png
[20160527151249674]: https://img-blog.csdn.net/20160527151249674
[20160527151253721]: /images/20220722/73648d3d00724b6ebe5bde1434b3dc55.png