opencv::直方图计算

直方图概念

  上述直方图概念是基于图像像素值,其实对图像梯度、每个像素的角度、等一切图像的属性值,我们都可以建立直方图。
        这个才是直方图的概念真正意义,不过是基于图像像素灰度直方图是最常见的.

 

直方图最常见的几个属性:
- dims 表示维度,对灰度图像来说只有一个通道值dims=1
- bins 表示在维度中子区域大小划分,bins=256,划分为256个级别
- range 表示值得范围,灰度值范围为[0~255]之间
// 把多通道图像分为多个单通道图像
split(
  const Mat &src, //输入图像
  Mat* mvbegin
)// 输出的通道图像数组

calcHist(
  const Mat* images,    //输入图像指针
  int images,        // 图像数目
  const int* channels,   // 通道数
  InputArray mask,      // 输入mask,可选,不用
  OutputArray hist,      //输出的直方图数据
  int dims,          // 维数
  const int* histsize,    // 直方图级数
  const float* ranges,   // 值域范围
  bool uniform,       // true by default
  bool accumulate      // false by defaut
)
int main(int argc, char** argv) {
    Mat src = imread(STRPAHT2);
    if (!src.data) {
        printf("could not load image...\n");
        return -1;
    }
    // 分通道显示
    vector<Mat> bgr_planes;
    split(src, bgr_planes);
    //imshow("single channel 0", bgr_planes[0]);
    //imshow("single channel 1", bgr_planes[1]);
    //imshow("single channel 2", bgr_planes[2]);

    
    // 计算直方图
    int histSize = 256;
    float range[] = { 0, 256 };
    const float *histRanges = { range };
    Mat b_hist, g_hist, r_hist;
    calcHist(&bgr_planes[0], 1, 0, Mat(), b_hist, 1, &histSize, &histRanges, true, false);
    calcHist(&bgr_planes[1], 1, 0, Mat(), g_hist, 1, &histSize, &histRanges, true, false);
    calcHist(&bgr_planes[2], 1, 0, Mat(), r_hist, 1, &histSize, &histRanges, true, false);

    // 归一化
    int hist_h = 400;
    int hist_w = 512;
    int bin_w = hist_w / histSize;
    Mat histImage(hist_w, hist_h, CV_8UC3, Scalar(0, 0, 0));
    normalize(b_hist, b_hist, 0, hist_h, NORM_MINMAX, -1, Mat());
    normalize(g_hist, g_hist, 0, hist_h, NORM_MINMAX, -1, Mat());
    normalize(r_hist, r_hist, 0, hist_h, NORM_MINMAX, -1, Mat());

    // render histogram chart
    for (int i = 1; i < histSize; i++) {
        line(histImage, Point((i - 1)*bin_w, hist_h - cvRound(b_hist.at<float>(i - 1))),
            Point((i)*bin_w, hist_h - cvRound(b_hist.at<float>(i))), Scalar(255, 0, 0), 2, LINE_AA);

        line(histImage, Point((i - 1)*bin_w, hist_h - cvRound(g_hist.at<float>(i - 1))),
            Point((i)*bin_w, hist_h - cvRound(g_hist.at<float>(i))), Scalar(0, 255, 0), 2, LINE_AA);

        line(histImage, Point((i - 1)*bin_w, hist_h - cvRound(r_hist.at<float>(i - 1))),
            Point((i)*bin_w, hist_h - cvRound(r_hist.at<float>(i))), Scalar(0, 0, 255), 2, LINE_AA);
    }
    imshow("OUTPUT_T", histImage);
    
    waitKey(0);
    return 0;
}

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转载自www.cnblogs.com/osbreak/p/11492886.html