【测试环境】

vs2019

opencv==4.8.0

【效果演示】

【核心实现代码】

#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)
#define M_PI 3.14
/**
 * 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;
}



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);
}

 【完整演示源码下载地址】

https://download.csdn.net/download/FL1623863129/89633007