数字图像水平镜像,垂直镜像和平移的matlab编程.docx

(x0,y0)为原图像上一点,图像水平平移量为tx,垂直平移量为ty,平移后的点为(x1,y1)x1=x0+tx;y1=y0+ty,转换后x0=x1-tx;y0=y1-ty这样平移后的图像上的每一点都可以在原图像中找到对应的点,可以根据x0和y0的值,判断原来的点是否在图像中,如果超出了原来图像的范围,就把点(x1,y1)的值设置成0(黑色)和255(白色). int OriginX; int OriginY; for(int i=0;iheight;i+) for(int j=0;jwidth;j+) OriginX=j-m_XOffset; OriginY=i-m_YOffset; /if(OriginX0)&(OriginXwidth)&(OriginY0)&(OriginYheight) if(OriginX0 | OriginYimageData+i*tran-widthStep)j=0; else (uchar *)(tran-imageData+i*tran-widthStep)j=(uchar *)(gray-imageData+OriginY*gray-widthStep)OriginX; 镜像原理 for(int i=0;iheight;i+) for(int j=0;jwidth;j+) OriginX=(gray-width-j); OriginY=i; (uchar *)(tran-imageData+i*tran-widthStep)j=(uchar *)(gray-imageData+OriginY*gray-widthStep)OriginX; 转置,在构建目标图时,要高度值和宽度值进行互换,转换时,目标坐标进行互换！ gray=cvCreateImage(cvSize(plmg-width,plmg-height),IPL_DEPTH_8U,1); tran=cvCreateImage(cvSize(gray-height,gray-width),IPL_DEPTH_8U,1); cvCvtColor(plmg,gray,CV_BGR2GRAY); int OriginX; int OriginY; for(int i=0;iheight;i+) for(int j=0;jwidth;j+) OriginX=i; OriginY=j; /(uchar *)(tran-imageData+i*tran-widthStep)j=(uchar *)(tran-imageData+OriginY*tran-widthStep)OriginX; (uchar *)(tran-imageData+i*tran-widthStep)j=(uchar *)(gray-imageData+OriginY*gray-widthStep)OriginX; 扩大,缩放的算法 plmg=cvLoadImage(lpszPathName,-1); gray=cvCreateImage(cvSize(plmg-width,plmg-height),IPL_DEPTH_8U,1); tran=cvCreateImage(cvSize(int)(gray-width*fXZoomRatio+0.5), (int)(gray-height*fYZoomRatio+0.5),IPL_DEPTH_8U,1); /首先要设定缩放后的大小,加上0.5是为了四舍五入. cvCvtColor(plmg,gray,CV_BGR2GRAY); float OriginX; float OriginY; for(int i=0;iheight;i+) for(int j=0;jwidth;j+) OriginX=j/fXZoomRatio+0.5;/原始坐标也要进行四舍五入 OriginY=i/fYZoomRatio+0.5; (uchar *)(tran-imageData+i*tran-widthStep)j=(uchar *)(gray-imageData+(int)OriginY)*gray-widthStep)(int)OriginX;/用的是领近插值法 cvNamedWindow(Image,1); cvShowImage(Image,tran);旋转的算法x0=x1cos(Q)+y1sin(Q)-ccos(Q)-dsin(Q)+ay0=-x1sin(Q)+y1cos(Q)+csin(Q)-dcos(Q)+b旋转以后图像会变大,先以原图像中心为坐标系原点,求得原图像四个点的坐标,就可以求得新图像的宽度和高度,以这两个参数设置输出的参数.用以上两个公式计算原始图像和输出图像的匹配点. LONG i0; LONG j0; IplImage* Img; IplImage* gray; IplImage* dst; Img=cvLoadImage(lpszPathName,-1); gray=cvCreateImage(cvSize(Img-width,Img-height),IPL_DEPTH_8U,1); /dst=cvCreateImage(cvSize(Img-width,Img-height),IPL_DEPTH_8U,1); cvCvtColor(Img,gray,CV_BGR2GRAY); LONG lWidth=Img-width; LONG lHeight=Img-height;/原始图像的高和宽像素值 float fSina=0.5; float fCosa=0.866; / 源图四个角的坐标（以图像中心为坐标系原点） float fSrcX1,fSrcY1,fSrcX2,fSrcY2,fSrcX3,fSrcY3,fSrcX4,fSrcY4; / 旋转后四个角的坐标（以图像中心为坐标系原点） float fDstX1,fDstY1,fDstX2,fDstY2,fDstX3,fDstY3,fDstX4,fDstY4; / 计算原图的四个角的坐标（以图像中心为坐标系原点） fSrcX1 = (float) (- (lWidth - 1) / 2); fSrcY1 = (float) ( (lHeight - 1) / 2); fSrcX2 = (float) ( (lWidth - 1) / 2); fSrcY2 = (float) ( (lHeight - 1) / 2); fSrcX3 = (float) (- (lWidth - 1) / 2); fSrcY3 = (float) (- (lHeight - 1) / 2); fSrcX4 = (float) ( (lWidth - 1) / 2); fSrcY4 = (float) (- (lHeight - 1) / 2); / 计算新图四个角的坐标（以图像中心为坐标系原点） fDstX1 = fCosa * fSrcX1 + fSina * fSrcY1; fDstY1 = -fSina * fSrcX1 + fCosa * fSrcY1; fDstX2 = fCosa * fSrcX2 + fSina * fSrcY2; fDstY2 = -fSina * fSrcX2 + fCosa * fSrcY2; fDstX3 = fCosa * fSrcX3 + fSina * fSrcY3; fDstY3 = -fSina * fSrcX3 + fCosa * fSrcY3; fDstX4 = fCosa * fSrcX4 + fSina * fSrcY4; fDstY4 = -fSina * fSrcX4 + fCosa * fSrcY4; / 计算旋转后的图像实际宽度 LONG lNewWidth = (LONG)(max(fabs(fDstX4 - fDstX1), fabs(fDstX3 - fDstX2) + 0.5); / 计算旋转后的图像高度 LONG lNewHeight = (LONG)(max(fabs(fDstY4 - fDstY1), fabs(fDstY3 - fDstY2) + 0.5); dst=cvCreateImage(cvSize(lNewWidth,lNewHeight),IPL_DEPTH_8U,1); float f1 = (float) (-0.5 * (lNewWidth - 1) * fCosa - 0.5 * (lNewHeight - 1) * fSina + 0.5 * (lWidth - 1); float f2 = (float) ( 0.5 * (lNewWidth - 1) * fSina - 0.5 * (lNewHeight - 1) * fCosa + 0.5 * (lHeight - 1); for(int i=0;iheight;i+) for(int j=0;jwidth;j+) / 计算该象素在源DIB中的坐标 i0 = (LONG) (-(float) j) * fSina + (float) i) * fCosa + f2 + 0.5); j0 = (LONG) ( (float) j) * fCosa + (float) i) * fSina + f1 + 0.5)