OpenCV访问图像像素的方法收集以及自己实践中得体会
OpenCV访问图像像素, 数组元素等方法收集访问图像像素的一些方法。
* Indirect access: (General, but inefficient, access to any type image)
o For a single-channel byte image:
IplImage* img = cvCreateImage( cvSize(640,480), IPL_DEPTH_8U, 1);
CvScalar s;
s=cvGet2D(img,i,j); // get the (i,j) pixel value
printf("intensity=%f\n",s.val[0]);
s.val[0]=111;
cvSet2D(img,i,j,s); // set the (i,j) pixel value
o For a multi-channel float (or byte) image:
IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3);
CvScalar s;
s=cvGet2D(img,i,j); // get the (i,j) pixel value
printf("B=%f, G=%f, R=%f\n",s.val[0],s.val[1],s.val[2]);
s.val[0]=111;
s.val[1]=111;
s.val[2]=111;
cvSet2D(img,i,j,s); // set the (i,j) pixel value
评论：以上方法都使用了opencv内置的函数cvGet2D()和cvSet2D()。本人亲测，这两个函数有缺陷，容易引发“该内存不能为read”的错误。
* Direct access: (Efficient access, but error prone)
o For a single-channel byte image:
IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1);
((uchar *)(img->imageData + i*img->widthStep))[j]=111;
o For a multi-channel byte image:
IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3);
((uchar *)(img->imageData + i*img->widthStep))[j*img->nChannels + 0]=111; // B
((uchar *)(img->imageData + i*img->widthStep))[j*img->nChannels + 1]=112; // G
((uchar *)(img->imageData + i*img->widthStep))[j*img->nChannels + 2]=113; // R
o For a multi-channel float image:
IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3);
((float *)(img->imageData + i*img->widthStep))[j*img->nChannels + 0]=111; // B
((float *)(img->imageData + i*img->widthStep))[j*img->nChannels + 1]=112; // G
((float *)(img->imageData + i*img->widthStep))[j*img->nChannels + 2]=113; // R
评论：以上方法是最常见的，也是访问速度最快的。
* Direct access using a pointer: (Simplified and efficient access under limiting assumptions)
o For a single-channel byte image:
IplImage* img = cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1);
int height = img->height;
int width = img->width;
int step = img->widthStep/sizeof(uchar);
uchar* data = (uchar *)img->imageData;
data[i*step+j] = 111;
o For a multi-channel byte image:
IplImage* img = cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3);
int height = img->height;
int width = img->width;
int step = img->widthStep/sizeof(uchar);
int channels = img->nChannels;
uchar* data = (uchar *)img->imageData;
data[i*step+j*channels+k] = 111;
o For a multi-channel float image (assuming a 4-byte alignment):
IplImage* img = cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3);
int height = img->height;
int width = img->width;
int step = img->widthStep/sizeof(float);
int channels = img->nChannels;
float * data = (float *)img->imageData;
data[i*step+j*channels+k] = 111;
* Direct access using a c++ wrapper: (Simple and efficient access)
o Define a c++ wrapper for single-channel byte images, multi-channel byte images, and multi-channel float images:
template<class T> class Image
{
private:
IplImage* imgp;
public:
Image(IplImage* img=0) {imgp=img;}
~Image(){imgp=0;}
void operator=(IplImage* img) {imgp=img;}
inline T* operator[](const int rowIndx) {
return ((T *)(imgp->imageData + rowIndx*imgp->widthStep));}
};
typedef struct{
unsigned char b,g,r;
} RgbPixel;
typedef struct{
float b,g,r;
} RgbPixelFloat;
typedef Image<RgbPixel> RgbImage;
typedef Image<RgbPixelFloat> RgbImageFloat;
typedef Image<unsigned char> BwImage;
typedef Image<float> BwImageFloat;
o For a single-channel byte image:
IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1);
BwImage imgA(img);
imgA[i][j] = 111;
o For a multi-channel byte image:
IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3);
RgbImage imgA(img);
imgA[i][j].b = 111;
imgA[i][j].g = 111;
imgA[i][j].r = 111;
o For a multi-channel float image:
IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3);
RgbImageFloat imgA(img);
imgA[i][j].b = 111;
imgA[i][j].g = 111;
imgA[i][j].r = 111;