opencv中的图像线性发大

/* 程序名：hello.c 功能：从磁盘中读入图像文件，并将图像显示在屏幕上 */ #include "cv.h" #include "highgui.h" int main( int argc, char** argv ) { IplImage *img; //Original image IplImage *img_s; //Scaled image int i,j; double xm,ym; unsigned char vff0,vff1,vff2,vcf0,vcf1,vcf2,vfc0,vfc1,vfc2,vcc0,vcc1,vcc2; unsigned char v0,v1,v2; double xs=1.5,ys=1.3; //Load the original image img=cvLoadImage("lena.jpg",1); //Apply memory for scaled image img_s=cvCreateImage(cvSize((int)img->width*xs,(int)img->height*ys),img->depth,img->nChannels); //Scale by linear interpolation for(i=0;i<img_s->height;i++){ for(j=0;j<img_s->width;j++){ //Middle pixel xm=(img->width-1)*j/(double)img_s->width; ym=(img->height-1)*i/(double)img_s->height; //找到对应的原图像中的点 //4 neighbor pixels of 3 color vff0=img->imageData[((int)floor(ym))*img->widthStep+((int)floor(xm))*img->nChannels+0]; //某点在原图中并不对应一点，可能是小数，所以对应四个点 vff1=img->imageData[((int)floor(ym))*img->widthStep+((int)floor(xm))*img->nChannels+1]; vff2=img->imageData[((int)floor(ym))*img->widthStep+((int)floor(xm))*img->nChannels+2]; vcf0=img->imageData[((int)floor(ym))*img->widthStep+((int)ceil(xm))*img->nChannels+0]; //floor向下取整,ceil向上取整 vcf1=img->imageData[((int)floor(ym))*img->widthStep+((int)ceil(xm))*img->nChannels+1]; vcf2=img->imageData[((int)floor(ym))*img->widthStep+((int)ceil(xm))*img->nChannels+2]; vfc0=img->imageData[((int)ceil(ym))*img->widthStep+((int)floor(xm))*img->nChannels+0]; vfc1=img->imageData[((int)ceil(ym))*img->widthStep+((int)floor(xm))*img->nChannels+1]; vfc2=img->imageData[((int)ceil(ym))*img->widthStep+((int)floor(xm))*img->nChannels+2]; vcc0=img->imageData[((int)ceil(ym))*img->widthStep+((int)ceil(xm))*img->nChannels+0]; vcc1=img->imageData[((int)ceil(ym))*img->widthStep+((int)ceil(xm))*img->nChannels+1]; vcc2=img->imageData[((int)ceil(ym))*img->widthStep+((int)ceil(xm))*img->nChannels+2]; //Perform linear interpolation v0=vff0+(vcf0-vff0)*(xm-(int)xm) +(vfc0+(vcc0-vfc0)*(xm-(int)xm)-vff0-(vcf0-vff0)*(xm-(int)xm))*(ym-(int)ym); //比如xm=3.4，ym=2.5，则原图中有（3，2）（4，2）（3，3）（4，3） v1=vff1+(vcf1-vff1)*(xm-(int)xm) //根据这四点算出（3.4，2.5）的值 +(vfc1+(vcc1-vfc1)*(xm-(int)xm)-vff1-(vcf1-vff1)*(xm-(int)xm))*(ym-(int)ym); v2=vff2+(vcf2-vff2)*(xm-(int)xm) +(vfc2+(vcc2-vfc2)*(xm-(int)xm)-vff2-(vcf2-vff2)*(xm-(int)xm))*(ym-(int)ym); //Set pixel of scaled image img_s->imageData[i*img_s->widthStep+j*img_s->nChannels+0]=v0; img_s->imageData[i*img_s->widthStep+j*img_s->nChannels+1]=v1; img_s->imageData[i*img_s->widthStep+j*img_s->nChannels+2]=v2; } } cvNamedWindow( "renwu11", 1 ); //创建窗口 cvShowImage( "renwu11", img_s ); cvWaitKey(0); //等待按键 cvDestroyWindow( "renwu" );//销毁窗口 cvReleaseImage( &img_s ); //释放图像 return 0; }