OpenCV（5） 对比度和亮度

 

公式：


两个参数 \alpha > 0 和 \beta 一般称作 增益 和 偏置 参数。我们往往用这两个参数来分别控制 对比度 和 亮度 。

 

#include "stdafx.h"

#include<iostream>

#include<thread>

#include<vector>

#include <opencv2/core/core.hpp>

#include <opencv2/contrib/contrib.hpp>

#include <opencv2/highgui/highgui.hpp>

#include <opencv2/imgproc/imgproc.hpp>

#include <opencv2/objdetect/objdetect.hpp>

 
using
namespace cv;

using
namespace std;

 
int g_slider_position = 0, g_slider_position2 = 0;

Mat image;

Mat new_image;

double alpha, beta;

 
void onTrackingbarSlide(int pos)

{

   new_image = Mat::zeros(image.size(), image.type());

   beta = pos;

   for (int y = 0; y < image.rows; y++)

   {

      for (int x = 0; x < image.cols; x++)

      {

         for (int c = 0; c < 3; c++)

         {

            //saturate_cast 防止数据溢出

            new_image.at<Vec3b>(y, x)[c] = saturate_cast<uchar>(alpha*(image.at<Vec3b>(y, x)[c]) + beta);

         }

      }

   }

 
   imshow("New Image", new_image);

}

 
void onTrackingbarSlide2(int pos)

{

   new_image = Mat::zeros(image.size(), image.type());

 
   alpha = (double)pos / 10.0;

 
   for (int y = 0; y < image.rows; y++)

   {

      for (int x = 0; x < image.cols; x++)

      {

         for (int c = 0; c < 3; c++)

         {

            //saturate_cast 防止数据溢出

            new_image.at<Vec3b>(y, x)[c] = saturate_cast<uchar>(alpha*(image.at<Vec3b>(y, x)[c]) + beta);

         }

      }

   }

 
   imshow("New Image", new_image);

}

 
int _tmain(int argc, _TCHAR* argv[])

{

   /// 读入用户提供的图像

   image = imread("E:\\myImage\\sql.png");

 
   //初始化为0的数组

   Mat new_image = Mat::zeros(image.size(), image.type());

 
   /// 初始化

   cout << "* Enter the alpha value [1.0-3.0]: ";

   cin >> alpha;

   cout << "* Enter the beta value [0-100]: ";

   cin >> beta;

 
   /// 创建窗口

   namedWindow("Original Image", 1); // 1:WINDOW_AUTOSIZE

   namedWindow("New Image", 1);

 
   cvCreateTrackbar("亮度（增益）", "New Image", &g_slider_position, 100, onTrackingbarSlide);

   cvCreateTrackbar("对比度（偏置）", "New Image", &g_slider_position2, 30, onTrackingbarSlide2);

 
   /// 执行运算 new_image(i,j) = alpha*image(i,j) + beta

   for (int y = 0; y < image.rows; y++)

   {

      for (int x = 0; x < image.cols; x++)

      {

         for (int c = 0; c < 3; c++)

         {

            //saturate_cast 防止数据溢出

            new_image.at<Vec3b>(y, x)[c] = saturate_cast<uchar>(alpha*(image.at<Vec3b>(y, x)[c]) + beta);

         }

      }

   }

 
   /// 显示图像

   imshow("Original Image", image);

   imshow("New Image", new_image);

 
   /// 等待用户按键

   waitKey();

   return 0;

}

 

 



参考：

http://www.opencv.org.cn/opencvdoc/2.3.2/html/doc/tutorials/core/basic_linear_transform/basic_linear_transform.html#basic-linear-transform

http://blog.csdn.net/mjlsuccess/article/details/12401839