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*);
//歸一化處理
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);
/*
參數說明 src 輸入數組; dst 輸出數組,數組的大小和原數組一致; alpha 1,用來規範值,2.規範範圍,並且是下限; beta 只用來規範範圍並且是上限; norm_type 歸一化選擇的數學公式類型; dtype 當為負,輸出在大小深度通道數都等於輸入,當為正,輸出只在深度與輸如不同,不同的地方遊dtype決定; mark 掩碼。選擇感興趣區域,選定後只能對該區域進行操作。 */
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;
}
Opencv normalize