用OpenCV实现Photoshop算法(五): 亮度对比度调整

系列文章：
用OpenCV实现Photoshop算法(一):
图像旋转

用OpenCV实现Photoshop算法(二):
图像剪切

用OpenCV实现Photoshop算法(三):
曲线调整
用OpenCV实现Photoshop算法(四): 色阶调整
用OpenCV实现Photoshop算法(五):
亮度对比度调整
用OpenCV实现Photoshop算法(六):
变为黑白图像
用OpenCV实现Photoshop算法(七):
调整色相饱和度
用OpenCV实现Photoshop算法(八):
可选颜色
用OpenCV实现Photoshop算法(九): 高反差保留




五、亮度对比度调整

（一）算法
　　亮度对比度调整的算法，我在网上找了很多篇，个人觉得以下这个算法效果较好，比较接近Photoshop的效果。
Algorithm of Brightness Contrast transformation
The formula is:
y = [x - 127.5 * (1 - B)] * k + 127.5 * (1 + B);

x is the input pixel value
y is the output pixel value
B is brightness, value range is [-1,1]
k is used to adjust contrast
k = tan( (45 + 44 * c) / 180 * PI );
c is contrast, value range is [-1,1]

于是，用OpenCV C++编写了一个 adjustBrightnessContrast()函数，可同时调整亮度、对比度。

（二）源码及例程

例程如下，　其中包含adjustBrightnessContrast()函数。

#include <iostream>
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"

using namespace std;
using namespace cv;

#define SWAP(a, b, t)  do { t = a; a = b; b = t; } while(0)
#define CLIP_RANGE(value, min, max)  ( (value) > (max) ? (max) : (((value) < (min)) ? (min) : (value)) )
#define COLOR_RANGE(value)  CLIP_RANGE(value, 0, 255)

/**
* Adjust Brightness and Contrast
*
* @param src [in] InputArray
* @param dst [out] OutputArray
* @param brightness [in] integer, value range [-255, 255]
* @param contrast [in] integer, value range [-255, 255]
*
* @return 0 if success, else return error code
*/
int adjustBrightnessContrast(InputArray src, OutputArray dst, int brightness, int contrast)
{
Mat input = src.getMat();
if( input.empty() ) {
return -1;
}

dst.create(src.size(), src.type());
Mat output = dst.getMat();

brightness = CLIP_RANGE(brightness, -255, 255);
contrast = CLIP_RANGE(contrast, -255, 255);

/**
Algorithm of Brightness Contrast transformation
The formula is:
y = [x - 127.5 * (1 - B)] * k + 127.5 * (1 + B);

x is the input pixel value
y is the output pixel value
B is brightness, value range is [-1,1]
k is used to adjust contrast
k = tan( (45 + 44 * c) / 180 * PI );
c is contrast, value range is [-1,1]
*/

double B = brightness / 255.;
double c = contrast / 255. ;
double k = tan( (45 + 44 * c) / 180 * M_PI );

Mat lookupTable(1, 256, CV_8U);
uchar *p = lookupTable.data;
for (int i = 0; i < 256; i++)
p[i] = COLOR_RANGE( (i - 127.5 * (1 - B)) * k + 127.5 * (1 + B) );

LUT(input, lookupTable, output);

return 0;
}

//=====主程序开始====

static string window_name = "photo";
static Mat src;
static int brightness = 255;
static int contrast = 255;

static void callbackAdjust(int , void *)
{
Mat dst;
adjustBrightnessContrast(src, dst, brightness - 255, contrast - 255);
imshow(window_name, dst);
}

int main()
{
src = imread("building.jpg");

if ( !src.data ) {
cout << "error read image" << endl;
return -1;
}

namedWindow(window_name);
createTrackbar("brightness", window_name, &brightness, 2*brightness, callbackAdjust);
createTrackbar("contrast", window_name, &contrast, 2*contrast, callbackAdjust);
callbackAdjust(0, 0);

waitKey();

return 0;

}

运行效果：

原图：



调整参数，　实施亮度对比度调整后：



系列文章：
用OpenCV实现Photoshop算法(一):
图像旋转

用OpenCV实现Photoshop算法(二):
图像剪切

用OpenCV实现Photoshop算法(三):
曲线调整
用OpenCV实现Photoshop算法(四): 色阶调整
用OpenCV实现Photoshop算法(五):
亮度对比度调整