使用OpenCV将RGB图像分为红色，绿色和蓝色分量

June 13, 2020

这个小型的OpenCV程序演示了如何将RGB图像分为R，G和B分量。该程序是用低级编程编写的，因为OpenCV中有内置功能，可以使此代码更高效。但是，此示例加深了对如何将图像拆分为像素矩阵以及如何分别操纵每个像素的理解。

写代码

#include 
#include "cv.h"
#include "highgui.h"

using namespace std;

int main( int argc, char** argv )

{
//load color img specified by first argument
//IplImage *img = cvLoadImage( argv[1]);
IplImage *img = cvLoadImage
(argv[1], CV_LOAD_IMAGE_COLOR );


IplImage *red = cvCreateImage

(cvSize(img->width, img->height ),
img->depth, img->nChannels );

IplImage *green = cvCreateImage
(cvSize(img->width, img->height ),
img->depth, img->nChannels );

IplImage *blue = cvCreateImage
(cvSize(img->width, img->height ),
img->depth, img->nChannels );



// setup the pointer to access img data 
uchar *pImg   = ( uchar* )img->imageData;

// setup pointer to write data 
uchar *pRed   = ( uchar* )red->imageData;
uchar *pGreen = ( uchar* )green->imageData;
uchar *pBlue  = ( uchar* )blue->imageData;    



int i, j, rED, gREEN, bLUE, byte;
for( i = 0 ; i < img->height ; i++ ) 
{

  for( j = 0 ; j < img->width ; j++ ) 
  {
  rED = pImg[i*img->widthStep + j*img->nChannels + 2];

  gREEN = pImg[i*img->widthStep + j*img->nChannels + 1];
  bLUE = pImg[i*img->widthStep + j*img->nChannels + 0];
  // RED

  pRed[i*img->widthStep + j*img->nChannels + 2] = rED;
  // GREEN
  pGreen[i*img->widthStep + j*img->nChannels + 1] = gREEN;

  // BLUE
  pBlue[i*img->widthStep + j*img->nChannels + 0] = bLUE;
  }
}
// save images

cvSaveImage( argv[2], red );
cvSaveImage( argv[3], green );
cvSaveImage( argv[4], blue );

return 0;

}

编译

g++ `pkg-config opencv --cflags --libs` \ 
separate-RGB.cpp -o separate-RGB

用法

./separate-RGB img.png red.png green.png blue.png