【Opencv】直方图函数 calchist()

calchist函数需要包含头文件

#include <opencv2/imgproc/imgproc.hpp>

函数声明(三个重载 calchist函数)：

//! computes the joint dense histogram for a set of images.
CV_EXPORTS void calcHist( const Mat* images, int nimages,
                          const int* channels, InputArray mask,
                          OutputArray hist, int dims, const int* histSize,
                          const float** ranges, bool uniform=true, bool accumulate=false );
 
//! computes the joint sparse histogram for a set of images.
CV_EXPORTS void calcHist( const Mat* images, int nimages,
                          const int* channels, InputArray mask,
                          SparseMat& hist, int dims,
                          const int* histSize, const float** ranges,
                          bool uniform=true, bool accumulate=false );
 
CV_EXPORTS_W void calcHist( InputArrayOfArrays images,
                            const vector<int>& channels,
                            InputArray mask, OutputArray hist,
                            const vector<int>& histSize,
                            const vector<float>& ranges,
                            bool accumulate=false );

官方文档：

The functions calcHist calculate the histogram of one or more arrays. The elements of a tuple used to increment a histogram bin are taken from the corresponding input arrays at the same location. The sample below shows how to compute a 2D Hue-Saturation histogram for a color image.

Parameters:

images – Source arrays. They all should have the same depth, CV_8U or CV_32F , and the same size. Each of them can have an arbitrary number of channels. nimages – Number of source images. channels – List of the dims channels used to compute the histogram. The first array channels are numerated from 0 to images[0].channels()-1 , the second array channels are counted from images[0].channels() to images[0].channels() + images[1].channels()-1, and so on. mask – Optional mask. If the matrix is not empty, it must be an 8-bit array of the same size as images[i] . The non-zero mask elements mark the array elements counted in the histogram. hist – Output histogram, which is a dense or sparse dims -dimensional array. dims – Histogram dimensionality that must be positive and not greater than CV_MAX_DIMS (equal to 32 in the current OpenCV version). histSize – Array of histogram sizes in each dimension. ranges – Array of the dims arrays of the histogram bin boundaries in each dimension. When the histogram is uniform ( uniform =true), then for each dimension i it is enough to specify the lower (inclusive) boundary  of the 0-th histogram bin and the upper (exclusive) boundary  for the last histogram bin histSize[i]-1 . That is, in case of a uniform histogram each of ranges[i] is an array of 2 elements. When the histogram is not uniform ( uniform=false ), then each of ranges[i] contains histSize[i]+1 elements: . The array elements, that are not between  and  , are not counted in the histogram. uniform – Flag indicating whether the histogram is uniform or not (see above). accumulate – Accumulation flag. If it is set, the histogram is not cleared in the beginning when it is allocated. This feature enables you to compute a single histogram from several sets of arrays, or to update the histogram in time.

释义：

images：源图像矩阵(可以多个，但必须满足一定条件：同等深度，同等大小，同种数据类型：CV_8U或CV_32F，通道数不需要一致)

nimages：源图像个数

channels：用来计算直方图

例程：

#include <cv.h>
#include <highgui.h>
 
using namespace cv;
 
int main( int argc, char** argv )
{
    Mat src, hsv;
    if( argc !=  || !(src=imread(argv[], )).data )
        return -;
 
    cvtColor(src, hsv, CV_BGR2HSV);
 
    // Quantize the hue to 30 levels
    // and the saturation to 32 levels
    int hbins = , sbins = ;
    int histSize[] = {hbins, sbins};
    // hue varies from 0 to 179, see cvtColor
    float hranges[] = { ,  };
    // saturation varies from 0 (black-gray-white) to
    // 255 (pure spectrum color)
    float sranges[] = { ,  };
    const float* ranges[] = { hranges, sranges };
    MatND hist;
    // we compute the histogram from the 0-th and 1-st channels
    int channels[] = {, };
 
    calcHist( &hsv, , channels, Mat(), // do not use mask
             hist, , histSize, ranges,
             true, // the histogram is uniform
             false );
    double maxVal=;
    minMaxLoc(hist, , &maxVal, , );
 
    int scale = ;
    Mat histImg = Mat::zeros(sbins*scale, hbins*, CV_8UC3);
 
    for( int h = ; h < hbins; h++ )
        for( int s = ; s < sbins; s++ )
        {
            float binVal = hist.at<float>(h, s);
            int intensity = cvRound(binVal*/maxVal);
            rectangle( histImg, Point(h*scale, s*scale),
                        Point( (h+)*scale - , (s+)*scale - ),
                        Scalar::all(intensity),
                        CV_FILLED );
        }
 
    namedWindow( "Source",  );
    imshow( "Source", src );
 
    namedWindow( "H-S Histogram",  );
    imshow( "H-S Histogram", histImg );
    waitKey();
}