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  • Opencv normalize

    #include <iostream>
    #include <opencv2/opencv.hpp>

    using namespace std;
    using namespace cv;

    Mat img1, img2, img3, img4, img5, img6, img_result, img_gray1, img_gray2, img_gray3, img_canny1, img_binary1, img_dist1, img_dist2, kernel_1, kernel_2, img_laplance, img_sharp;

    char win1[] = "window1";
    char win2[] = "window2";
    char win3[] = "window3";
    char win4[] = "window4";
    char win5[] = "window5";
    char win6[] = "window6";
    char win7[] = "window7";

    int thread_value = 100;
    int max_value = 255;
    RNG rng1(12345);
    RNG rng2(1235);

    double harris_min = 0;
    double harris_max = 0;

    int Demo_Normalize();
    void Demo_1(int, void*);

    //归一化处理
    int Demo_Normalize()
    {
      namedWindow(win1, CV_WINDOW_AUTOSIZE);
      //namedWindow(win2, CV_WINDOW_AUTOSIZE);
      //namedWindow(win3, CV_WINDOW_AUTOSIZE);

      img1 = imread("D://images//4//3.jpg");
      //img2 = imread("D://images//1//p5_1.jpg");
      if (img1.empty())
      {
        cout << "could not load image..." << endl;
        return 0;
      }
      imshow(win1, img1);

      /*

      参数说明
      src               输入数组;
      dst               输出数组,数组的大小和原数组一致;
      alpha           1,用来规范值,2.规范范围,并且是下限;
      beta             只用来规范范围并且是上限;
      norm_type   归一化选择的数学公式类型;
      dtype           当为负,输出在大小深度通道数都等于输入,当为正,输出只在深度与输如不同,不同的地方游dtype决定;
      mark            掩码。选择感兴趣区域,选定后只能对该区域进行操作。

      */
      normalize(img1, img2, 0, 1, NORM_MINMAX, -1, Mat());
      imshow(win2, img2*1000);

      return 0;
    }

    void Demo_1(int, void*)
    {
      

    }

    int main()
    {
      Demo_Normalize();

      waitKey(0);
      return 0;
    }

     

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  • 原文地址:https://www.cnblogs.com/herd/p/9742268.html
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