OpenCV2 计算直方图

我们仍然如前例一样，构建一个类来处理得到直方图。

我们来看看基本的类定义

#ifndef HISTOGRAM_H_#define HISTOGRAM_H_#include <opencv2/core/core.hpp>#include <opencv2/highgui/highgui.hpp>#include <opencv2/imgproc/imgproc.hpp>#include <iostream>#include <vector>class Histogram {private:    int histSize[1];    float hrangee[2];    const float* ranges[1];    int channels[1];protected:    cv::Mat getHistogram(const cv::Mat&);public:    Histogram();    cv::Mat getHistogramImage(const cv::Mat&, int channel = 0);};#endif /* HISTOGRAM_H_ */

类的实现

#include "Histogram.h"Histogram::Histogram() {    histSize[0] = 256;    hrangee[0] = 0.0;    hrangee[1] = 255.0;    ranges[0] = hrangee;    channels[0] = 0;}cv::Mat Histogram::getHistogram(const cv::Mat& image){    cv::MatND hist;    cv::calcHist(&image, 1, channels, cv::Mat(), hist, 1, histSize, ranges);    return hist;}cv::Mat Histogram::getHistogramImage(const cv::Mat& image, int channel){    std::vector<cv::Mat> planes;    cv::split(image,planes);    cv::Scalar color;    if(planes.size() == 1){        channel = 0;        color = cv::Scalar(0,0,0);    }else{        color = cv::Scalar(channel==0?255:0, channel==1?255:0, channel==2?255:0);    }    cv::MatND hist = getHistogram(planes[channel]);    double maxVal = 0;    double minVal = 0;    cv::minMaxLoc(hist, &minVal, &maxVal, 0, 0);    cv::Mat histImg(histSize[0], histSize[0], CV_8UC3, cv::Scalar(255,255,255));    int hpt = static_cast<int>(0.9*histSize[0]);    for(int h=0; h<histSize[0]-1; h++){        float binVal = hist.at<float>(h);        float binVal2 = hist.at<float>(h+1);        int intensity = static_cast<int>(binVal*hpt/maxVal);        int intensity2 = static_cast<int>(binVal2*hpt/maxVal);        cv::line(histImg, cv::Point(h,histSize[0]-intensity),                cv::Point(h,histSize[0]-intensity2), color);    }    return histImg;}

这里面要用的几个函数在这里列出：

C++:voidminMaxLoc(const SparseMat& src, double minVal, double maxVal, int minIdx=0, int maxIdx=0)

其作用是寻找一个矩阵中最大和最小值，并得到它们的位置

C++:voidsplit(const Mat& mtx, vector& mv)

把一个多通道矩阵分成几个单通道矩阵，在这里主要用于计算各通道的直方图

C++:voidcalcHist(const Mat arrays, int narrays, const int channels, InputArray mask, OutputArray hist, int dims, const int histSize, const float ranges, bool uniform=true, bool accumulate*=false)

计算直方图，各参数含义可在参考文档中查到

Parameters:

• arrays – Source arrays. They all should have the same depth,CV_8UorCV_32F, and the same size. Each of them can have an arbitrary number of channels.
• narrays – Number of source arrays.
• channels – List of thedimschannels used to compute the histogram. The first array channels are numerated from 0 toarrays[0].channels()-1, the second array channels are counted fromarrays[0].channels()toarrays[0].channels()+arrays[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 asarrays[i]. The non-zero mask elements mark the array elements counted in the histogram.
• hist – Output histogram, which is a dense or sparsedims-dimensional array.
• dims – Histogram dimensionality that must be positive and not greater thanCV_MAX_DIMS(equal to 32 in the current OpenCV version).
• histSize – Array of histogram sizes in each dimension.
• ranges – Array of thedimsarrays of the histogram bin boundaries in each dimension. When the histogram is uniform (uniform=true), then for each dimensioniit is enough to specify the lower (inclusive) boundary of the 0-th histogram bin and the upper (exclusive) boundary for the last histogram binhistSize[i]-1. That is, in case of a uniform histogram each ofranges[i]is an array of 2 elements. When the histogram is not uniform (uniform=false), then each ofranges[i]containshistSize[i]+1elements: . The array elements, that are not between and , are not counted in the histogram.
• uniform – Flag indicatinfg 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.

我们来看看主程序

#include "Histogram.h"int main(){    cv::Mat image = cv::imread("E:/Image/Lena.jpg");    Histogram h;    cv::namedWindow("Red");    cv::namedWindow("Blue");    cv::namedWindow("Green");    cv::namedWindow("Original");    cv::imshow("Original",image);    cv::imshow("Red",h.getHistogramImage(image,2));    cv::imshow("Green",h.getHistogramImage(image,1));    cv::imshow("Blue",h.getHistogramImage(image));    cv::waitKey(0);    return 0;}

运行效果如下：

原文链接: https://www.cnblogs.com/xianglan/archive/2011/08/03/2126092.html

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