本文主要是介绍Opencv C++图像处理：亮度+对比度+饱和度+高光+暖色调+阴影+漫画效果+白平衡+浮雕+羽化+锐化+颗粒感，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！
文章目录
- 一、多功能色彩调整
- 1.1、亮度
- 1.2、对比度
- 1.3、饱和度
- 1.4、高光
- 1.5、暖色调
- 1.6、阴影
- 1.7、漫画效果
- 1.8、白平衡-灰度世界
- 1.9、白平衡-完美反射
- 1.10、浮雕
- 1.11、羽化
- 1.12、锐化
- 1.13、颗粒感
- 二、实战案例
- 2.1、主函数
- 2.2、函数定义
更多详细信息请看：OpenCV专栏：翟天保Steven
一、多功能色彩调整
1.1、亮度
//--------------------------------------------------------------------------------
// 亮度与对比度
cv::Mat Brightness(cv::Mat src, float brightness, int contrast)
{cv::Mat dst;dst = cv::Mat::zeros(src.size(), src.type()); //新建空白模板：大小/类型与原图像一致，像素值全0。int height = src.rows; //获取图像高度int width = src.cols; //获取图像宽度float alpha = brightness; //亮度（0~1为暗，1~正无穷为亮）float beta = contrast; //对比度cv::Mat template1;src.convertTo(template1, CV_32F); //将CV_8UC1转换为CV32F1数据格式。for (int row = 0; row < height; row++){for (int col = 0; col < width; col++){if (src.channels() == 3){float b = template1.at<cv::Vec3f>(row, col)[0]; //获取通道的像素值（blue）float g = template1.at<cv::Vec3f>(row, col)[1]; //获取通道的像素值（green）float r = template1.at<cv::Vec3f>(row, col)[2]; //获取通道的像素值（red）//cv::saturate_cast<uchar>(vaule)：需注意，value值范围必须在0~255之间。dst.at<cv::Vec3b>(row, col)[0] = cv::saturate_cast<uchar>(b * alpha + beta); //修改通道的像素值（blue）dst.at<cv::Vec3b>(row, col)[1] = cv::saturate_cast<uchar>(g * alpha + beta); //修改通道的像素值（green）dst.at<cv::Vec3b>(row, col)[2] = cv::saturate_cast<uchar>(r * alpha + beta); //修改通道的像素值（red）}else if (src.channels() == 1){float v = src.at<uchar>(row, col); //获取通道的像素值（单）dst.at<uchar>(row, col) = cv::saturate_cast<uchar>(v * alpha + beta); //修改通道的像素值（单）//saturate_cast<uchar>：主要是为了防止颜色溢出操作。如果color<0，则color等于0；如果color>255，则color等于255。}}}return dst;
}
1.2、对比度
//--------------------------------------------------------------------------------
// 亮度与对比度
cv::Mat Brightness(cv::Mat src, float brightness, int contrast)
{cv::Mat dst;dst = cv::Mat::zeros(src.size(), src.type()); //新建空白模板：大小/类型与原图像一致，像素值全0。int height = src.rows; //获取图像高度int width = src.cols; //获取图像宽度float alpha = brightness; //亮度（0~1为暗，1~正无穷为亮）float beta = contrast; //对比度cv::Mat template1;src.convertTo(template1, CV_32F); //将CV_8UC1转换为CV32F1数据格式。for (int row = 0; row < height; row++){for (int col = 0; col < width; col++){if (src.channels() == 3){float b = template1.at<cv::Vec3f>(row, col)[0]; //获取通道的像素值（blue）float g = template1.at<cv::Vec3f>(row, col)[1]; //获取通道的像素值（green）float r = template1.at<cv::Vec3f>(row, col)[2]; //获取通道的像素值（red）//cv::saturate_cast<uchar>(vaule)：需注意，value值范围必须在0~255之间。dst.at<cv::Vec3b>(row, col)[0] = cv::saturate_cast<uchar>(b * alpha + beta); //修改通道的像素值（blue）dst.at<cv::Vec3b>(row, col)[1] = cv::saturate_cast<uchar>(g * alpha + beta); //修改通道的像素值（green）dst.at<cv::Vec3b>(row, col)[2] = cv::saturate_cast<uchar>(r * alpha + beta); //修改通道的像素值（red）}else if (src.channels() == 1){float v = src.at<uchar>(row, col); //获取通道的像素值（单）dst.at<uchar>(row, col) = cv::saturate_cast<uchar>(v * alpha + beta); //修改通道的像素值（单）//saturate_cast<uchar>：主要是为了防止颜色溢出操作。如果color<0，则color等于0；如果color>255，则color等于255。}}}return dst;
}
1.3、饱和度
//--------------------------------------------------------------------------------
// 饱和度
cv::Mat Saturation(cv::Mat src, int saturation)
{float Increment = saturation * 1.0f / 100;cv::Mat temp = src.clone();int row = src.rows;int col = src.cols;for (int i = 0; i < row; ++i){uchar *t = temp.ptr<uchar>(i);uchar *s = src.ptr<uchar>(i);for (int j = 0; j < col; ++j){uchar b = s[3 * j];uchar g = s[3 * j + 1];uchar r = s[3 * j + 2];float max = max3(r, g, b);float min = min3(r, g, b);float delta, value;float L, S, alpha;delta = (max - min) / 255;if (delta == 0)continue;value = (max + min) / 255;L = value / 2;if (L < 0.5)S = delta / value;elseS = delta / (2 - value);if (Increment >= 0){if ((Increment + S) >= 1)alpha = S;elsealpha = 1 - Increment;alpha = 1 / alpha - 1;t[3 * j + 2] =static_cast<uchar>( r + (r - L * 255) * alpha);t[3 * j + 1] = static_cast<uchar>(g + (g - L * 255) * alpha);t[3 * j] = static_cast<uchar>(b + (b - L * 255) * alpha);}else{alpha = Increment;t[3 * j + 2] = static_cast<uchar>(L * 255 + (r - L * 255) * (1 + alpha));t[3 * j + 1] = static_cast<uchar>(L * 255 + (g - L * 255) * (1 + alpha));t[3 * j] = static_cast<uchar>(L * 255 + (b - L * 255) * (1 + alpha));}}}return temp;
}
1.4、高光
//--------------------------------------------------------------------------------
// 高光
cv::Mat HighLight(cv::Mat src, int highlight)
{// 生成灰度图cv::Mat gray = cv::Mat::zeros(src.size(), CV_32FC1);cv::Mat f = src.clone();f.convertTo(f, CV_32FC3);std::vector<cv::Mat> pics;split(f, pics);gray = 0.299f*pics[2] + 0.587*pics[2] + 0.114*pics[0];gray = gray / 255.f;// 确定高光区cv::Mat thresh = cv::Mat::zeros(gray.size(), gray.type());thresh = gray.mul(gray);// 取平均值作为阈值cv::Scalar t = mean(thresh);cv::Mat mask = cv::Mat::zeros(gray.size(), CV_8UC1);mask.setTo(255, thresh >= t[0]);// 参数设置int max = 4;float bright = highlight / 100.0f / max;float mid = 1.0f + max * bright;// 边缘平滑过渡cv::Mat midrate = cv::Mat::zeros(src.size(), CV_32FC1);cv::Mat brightrate = cv::Mat::zeros(src.size(), CV_32FC1);for (int i = 0; i < src.rows; ++i){uchar *m = mask.ptr<uchar>(i);float *th = thresh.ptr<float>(i);float *mi = midrate.ptr<float>(i);float *br = brightrate.ptr<float>(i);for (int j = 0; j < src.cols; ++j){if (m[j] == 255){mi[j] = mid;br[j] = bright;}else {mi[j] = (mid - 1.0f) / t[0] * th[j] + 1.0f;br[j] = (1.0f / t[0] * th[j])*bright;}}}// 高光提亮，获取结果图cv::Mat result = cv::Mat::zeros(src.size(), src.type());for (int i = 0; i < src.rows; ++i){float *mi = midrate.ptr<float>(i);float *br = brightrate.ptr<float>(i);uchar *in = src.ptr<uchar>(i);uchar *r = result.ptr<uchar>(i);for (int j = 0; j < src.cols; ++j){for (int k = 0; k < 3; ++k){float temp = pow(float(in[3 * j + k]) / 255.f, 1.0f / mi[j])*(1.0 / (1 - br[j]));if (temp > 1.0f)temp = 1.0f;if (temp < 0.0f)temp = 0.0f;uchar utemp = uchar(255*temp);r[3 * j + k] = utemp;}}}return result;
}
1.5、暖色调
//--------------------------------------------------------------------------------
// 暖色调
cv::Mat ColorTemperature(cv::Mat src, int warm)
{cv::Mat result = src.clone();int row = src.rows;int col = src.cols;int level = warm/2;for (int i = 0; i < row; ++i){uchar* a = src.ptr<uchar>(i);uchar* r = result.ptr<uchar>(i);for (int j = 0; j < col; ++j){int R,G,B;// R通道R = a[j * 3 + 2];R = R + level;if (R > 255) {r[j * 3 + 2] = 255;}else if (R < 0) {r[j * 3 + 2] = 0;}else {r[j * 3 + 2] = R;}// G通道G = a[j * 3 + 1];G = G + level;if (G > 255) {r[j * 3 + 1] = 255;}else if (G < 0) {r[j * 3 + 1] = 0;}else {r[j * 3 + 1] = G;}// B通道B = a[j * 3];B = B - level;if (B > 255) {r[j * 3] = 255;}else if (B < 0) {r[j * 3] = 0;}else {r[j * 3] = B;}}}return result;
}
1.6、阴影
//--------------------------------------------------------------------------------
// 阴影
cv::Mat Shadow(cv::Mat src, int shadow)
{// 生成灰度图cv::Mat gray = cv::Mat::zeros(src.size(), CV_32FC1);cv::Mat f = src.clone();f.convertTo(f, CV_32FC3);std::vector<cv::Mat> pics;split(f, pics);gray = 0.299f*pics[2] + 0.587*pics[2] + 0.114*pics[0];gray = gray / 255.f;// 确定阴影区cv::Mat thresh = cv::Mat::zeros(gray.size(), gray.type()); thresh = (1.0f - gray).mul(1.0f - gray);// 取平均值作为阈值cv::Scalar t = mean(thresh);cv::Mat mask = cv::Mat::zeros(gray.size(), CV_8UC1);mask.setTo(255, thresh >= t[0]);// 参数设置int max = 4;float bright = shadow / 100.0f / max;float mid = 1.0f + max * bright;// 边缘平滑过渡cv::Mat midrate = cv::Mat::zeros(src.size(), CV_32FC1);cv::Mat brightrate = cv::Mat::zeros(src.size(), CV_32FC1);for (int i = 0; i < src.rows; ++i){uchar *m = mask.ptr<uchar>(i);float *th = thresh.ptr<float>(i);float *mi = midrate.ptr<float>(i);float *br = brightrate.ptr<float>(i);for (int j = 0; j < src.cols; ++j){if (m[j] == 255){mi[j] = mid;br[j] = bright;}else {mi[j] = (mid - 1.0f) / t[0] * th[j]+ 1.0f; br[j] = (1.0f / t[0] * th[j])*bright; }}}// 阴影提亮，获取结果图cv::Mat result = cv::Mat::zeros(src.size(), src.type());for (int i = 0; i < src.rows; ++i){float *mi = midrate.ptr<float>(i);float *br = brightrate.ptr<float>(i);uchar *in = src.ptr<uchar>(i);uchar *r = result.ptr<uchar>(i);for (int j = 0; j < src.cols; ++j){for (int k = 0; k < 3; ++k){float temp = pow(float(in[3 * j + k]) / 255.f, 1.0f / mi[j])*(1.0 / (1 - br[j]));if (temp > 1.0f)temp = 1.0f;if (temp < 0.0f)temp = 0.0f;uchar utemp = uchar(255*temp);r[3 * j + k] = utemp;}}}return result;
}
1.7、漫画效果
//--------------------------------------------------------------------------------
// 漫画效果
cv::Mat Cartoon(cv::Mat src, double clevel, int d, double sigma, int size)
{// 中值滤波cv::Mat m;cv::medianBlur(src, m, 7);// 提取轮廓cv::Mat c;clevel = cv::max(40., cv::min(80., clevel));cv::Canny(m, c, clevel, clevel *3);// 轮廓膨胀加深cv::Mat k = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(2, 2));cv::dilate(c, c, k);// 反转c = c / 255;c = 1 - c;// 类型转化cv::Mat cf;c.convertTo(cf, CV_32FC1);// 均值滤波cv::blur(cf, cf, cv::Size(5, 5));// 双边滤波cv::Mat srcb;d = cv::max(0, cv::min(10, d));sigma = cv::max(10., cv::min(250., sigma));cv::bilateralFilter(src, srcb, d, sigma, sigma);size = cv::max(10, cv::min(25, size));cv::Mat temp = srcb / size;temp = temp * size;// 通道合并cv::Mat c3;cv::Mat cannyChannels[] = { cf, cf, cf };cv::merge(cannyChannels, 3, c3);// 类型转化cv::Mat tempf;temp.convertTo(tempf, CV_32FC3);// 图像相乘cv::multiply(tempf, c3, tempf);// 类型转化tempf.convertTo(temp, CV_8UC3);return temp;
}
1.8、白平衡-灰度世界
//--------------------------------------------------------------------------------
// 白平衡-灰度世界
cv::Mat WhiteBalcane_Gray(cv::Mat src)
{cv::Mat result = src.clone();if (src.channels() != 3){std::cout << "The number of image channels is not 3." << std::endl;return result;}// 通道分离std::vector<cv::Mat> Channel;cv::split(src, Channel);// 计算通道灰度值均值double Bm = cv::mean(Channel[0])[0];double Gm = cv::mean(Channel[1])[0];double Rm = cv::mean(Channel[2])[0];double Km = (Bm + Gm + Rm) / 3;// 通道灰度值调整Channel[0] *= Km / Bm;Channel[1] *= Km / Gm;Channel[2] *= Km / Rm;// 合并通道cv::merge(Channel, result);return result;
}
1.9、白平衡-完美反射
//--------------------------------------------------------------------------------
// 白平衡-完美反射
cv::Mat WhiteBalcane_PRA(cv::Mat src)
{cv::Mat result = src.clone();if (src.channels() != 3){std::cout << "The number of image channels is not 3." << std::endl;return result;}// 通道分离std::vector<cv::Mat> Channel;cv::split(src, Channel);// 定义参数int row = src.rows;int col = src.cols;int RGBSum[766] = { 0 };uchar maxR, maxG, maxB;// 计算单通道最大值for (int i = 0; i < row; ++i){uchar *b = Channel[0].ptr<uchar>(i);uchar *g = Channel[1].ptr<uchar>(i);uchar *r = Channel[2].ptr<uchar>(i);for (int j = 0; j < col; ++j){int sum = b[j] + g[j] + r[j];RGBSum[sum]++;maxB = cv::max(maxB, b[j]);maxG = cv::max(maxG, g[j]);maxR = cv::max(maxR, r[j]);}}// 计算最亮区间下限Tint T = 0;int num = 0;int K = static_cast<int>(row * col * 0.1);for (int i = 765; i >= 0; --i){num += RGBSum[i];if (num > K){T = i;break;}}// 计算单通道亮区平均值double Bm = 0.0, Gm = 0.0, Rm = 0.0;int count = 0;for (int i = 0; i < row; ++i){uchar *b = Channel[0].ptr<uchar>(i);uchar *g = Channel[1].ptr<uchar>(i);uchar *r = Channel[2].ptr<uchar>(i);for (int j = 0; j < col; ++j){int sum = b[j] + g[j] + r[j];if (sum > T){Bm += b[j];Gm += g[j];Rm += r[j];count++;}}}Bm /= count;Gm /= count;Rm /= count;// 通道调整Channel[0] *= maxB / Bm;Channel[1] *= maxG / Gm;Channel[2] *= maxR / Rm;// 合并通道cv::merge(Channel, result);return result;
}
1.10、浮雕
//--------------------------------------------------------------------------------
// 浮雕
cv::Mat Relief(cv::Mat src)
{CV_Assert(src.channels() == 3);int row = src.rows;int col = src.cols;cv::Mat temp = src.clone();for (int i = 1; i < row-1; ++i){uchar *s1 = src.ptr<uchar>(i - 1);uchar *s2 = src.ptr<uchar>(i + 1);uchar *t = temp.ptr<uchar>(i);for (int j = 1; j < col-1; ++j){for (int k = 0; k < 3; ++k){int RGB = s1[3 * (j - 1) + k] - s2[3 * (j + 1) + k] + 128;if (RGB < 0)RGB = 0;if (RGB > 255)RGB = 255;t[3*j+k] =(uchar)RGB;}}}return temp;
}
1.11、羽化
//--------------------------------------------------------------------------------
// 羽化
cv::Mat Eclosion(cv::Mat src, cv::Point center, float level)
{if (level > 0.9)level = 0.9f;float diff = (1-level) * (src.rows / 2 * src.rows / 2 + src.cols / 2 * src.cols / 2);cv::Mat result = src.clone();for (int i = 0; i < result.rows; ++i){for (int j = 0; j < result.cols; ++j){float dx = float(center.x - j);float dy = float(center.y - i);float ra = dx * dx + dy * dy;float m = ((ra-diff) / diff * 255)>0? ((ra - diff) / diff * 255):0;int b = result.at<cv::Vec3b>(i, j)[0];int g = result.at<cv::Vec3b>(i, j)[1];int r = result.at<cv::Vec3b>(i, j)[2];b = (int)(b+ m);g = (int)(g + m);r = (int)(r + m);result.at<cv::Vec3b>(i, j)[0] = (b > 255 ? 255 : (b < 0 ? 0 : b));result.at<cv::Vec3b>(i, j)[1] = (g > 255 ? 255 : (g < 0 ? 0 : g));result.at<cv::Vec3b>(i, j)[2] = (r > 255 ? 255 : (r < 0 ? 0 : r));}}return result;
}
1.12、锐化
//--------------------------------------------------------------------------------
// 锐化
cv::Mat Sharpen(cv::Mat input, int percent, int type)
{cv::Mat result;cv::Mat s = input.clone();cv::Mat kernel;switch (type){case 0:kernel = (cv::Mat_<int>(3, 3) <<0, -1, 0,-1, 4, -1,0, -1, 0);case 1:kernel = (cv::Mat_<int>(3, 3) <<-1, -1, -1,-1, 8, -1,-1, -1, -1);default:kernel = (cv::Mat_<int>(3, 3) <<0, -1, 0,-1, 4, -1,0, -1, 0);}cv::filter2D(s, s, s.depth(), kernel);result = input + s * 0.01 * percent;return result;
}
1.13、颗粒感
//--------------------------------------------------------------------------------
// 颗粒感
cv::Mat Grainy(cv::Mat src, int level)
{int row = src.rows;int col = src.cols;if (level > 100)level = 100;if (level < 0)level = 0;cv::Mat result = src.clone();for (int i = 0; i < row; ++i){uchar *t = result.ptr<uchar>(i);for (int j = 0; j < col; ++j){for (int k = 0; k < 3; ++k){int temp = t[3 * j + k];temp += ((rand() % (2 * level)) - level);if (temp < 0)temp = 0;if (temp > 255)temp = 255;t[3 * j + k] = temp;}}}return result;
}
二、实战案例
2.1、主函数
#include<opencv2\opencv.hpp>
//using namespace cv;
//using namespace std;#define max2(a,b) (a>b?a:b)
#define max3(a,b,c) (a>b?max2(a,c):max2(b,c))
#define min2(a,b) (a<b?a:b)
#define min3(a,b,c) (a<b?min2(a,c):min2(b,c))//函数申明
cv::Mat Brightness(cv::Mat src, float brightness, int contrast); //亮度+对比度。
cv::Mat Saturation(cv::Mat src, int saturation); //饱和度
cv::Mat HighLight(cv::Mat src, int highlight); //高光
cv::Mat ColorTemperature(cv::Mat src, int warm); //暖色调
cv::Mat Shadow(cv::Mat src, int shadow); //阴影cv::Mat Sharpen(cv::Mat input, int percent, int type); //图像锐化
cv::Mat Grainy(cv::Mat src, int level); //颗粒感
cv::Mat Cartoon(cv::Mat src, double clevel, int d, double sigma, int size); //漫画效果
cv::Mat WhiteBalcane_PRA(cv::Mat src); //白平衡-完美反射算法（效果偏白）
cv::Mat WhiteBalcane_Gray(cv::Mat src); //白平衡-灰度世界算法（效果偏蓝）
cv::Mat Relief(cv::Mat src); //浮雕
cv::Mat Eclosion(cv::Mat src, cv::Point center, float level); //羽化int main(int argc, char* argv[])
{//（1）读取图像std::string img_path = "test.jpg";cv::Mat src = cv::imread(img_path, 1);//（2）判断图像是否读取成功if (!src.data){std::cout << "can't read image!" << std::endl;return -1;}float brightness_value = 1; //[0, 10] 亮度。暗~亮：[0, 1] ~ [1, 10]int contrast_value = 0; //[-100, 100] 对比度。int saturation_value = 0; //[-100, 100] 饱和度。int highlight_value = 0; //[-100, 100] 高光。int warm_value = 0; //[-100, 100] 暖色调。int shadow_value = 0; //[-100, 100] 阴影。int sharpen_value = 0; //[-100, 100] 锐化。[-1000000, 1000000]int grainy_value = 0; //[0, 100] 颗粒感。int eclosion_flag = 0; //[0, 1] 羽化。int cartoon_flag = 0; //[0, 1] 漫画效果。clevel阈值40-80，d阈值0-10，sigma阈值10-250，size阈值10-25int reflect_flag = 0; //[0, 1] 白平衡-完美反射。int world_flag = 0; //[0, 1] 白平衡-灰度世界。int relief_flag = 0; //[0, 1] 浮雕。cv::Mat dst = src.clone();if (brightness_value != 1)dst = Brightness(dst, brightness_value, 0);if (contrast_value != 0)dst = Brightness(dst, 1, contrast_value);if (saturation_value != 0)dst = Saturation(dst, saturation_value);if (highlight_value != 0)dst = HighLight(dst, highlight_value);if (warm_value != 0)dst = ColorTemperature(dst, warm_value);if (shadow_value != 0)dst = Shadow(dst, shadow_value);if (sharpen_value != 0)dst = Sharpen(dst, sharpen_value, 0);if (grainy_value != 0)dst = Grainy(dst, grainy_value);if (cartoon_flag != 0)dst = Cartoon(dst, 80, 5, 150, 20); //clevel阈值40-80，d阈值0-10，sigma阈值10-250，size阈值10-25说if (reflect_flag != 0)dst = WhiteBalcane_PRA(dst);if (world_flag != 0)dst = WhiteBalcane_Gray(dst);if (relief_flag != 0)dst = Relief(dst);if (eclosion_flag != 0)dst = Eclosion(dst, cv::Point(src.cols / 2, src.rows / 2), 0.8f);//（4）显示图像cv::imshow("src", src);cv::imshow("锐化", dst);cv::waitKey(0); //等待用户任意按键后结束暂停功能return 0;
}
2.2、函数定义
//--------------------------------------------------------------------------------
//调整对比度与亮度
cv::Mat Brightness(cv::Mat src, float brightness, int contrast)
{cv::Mat dst;dst = cv::Mat::zeros(src.size(), src.type()); //新建空白模板：大小/类型与原图像一致，像素值全0。int height = src.rows; //获取图像高度int width = src.cols; //获取图像宽度float alpha = brightness; //亮度（0~1为暗，1~正无穷为亮）float beta = contrast; //对比度cv::Mat template1;src.convertTo(template1, CV_32F); //将CV_8UC1转换为CV32F1数据格式。for (int row = 0; row < height; row++){for (int col = 0; col < width; col++){if (src.channels() == 3){float b = template1.at<cv::Vec3f>(row, col)[0]; //获取通道的像素值（blue）float g = template1.at<cv::Vec3f>(row, col)[1]; //获取通道的像素值（green）float r = template1.at<cv::Vec3f>(row, col)[2]; //获取通道的像素值（red）//cv::saturate_cast<uchar>(vaule)：需注意，value值范围必须在0~255之间。dst.at<cv::Vec3b>(row, col)[0] = cv::saturate_cast<uchar>(b * alpha + beta); //修改通道的像素值（blue）dst.at<cv::Vec3b>(row, col)[1] = cv::saturate_cast<uchar>(g * alpha + beta); //修改通道的像素值（green）dst.at<cv::Vec3b>(row, col)[2] = cv::saturate_cast<uchar>(r * alpha + beta); //修改通道的像素值（red）}else if (src.channels() == 1){float v = src.at<uchar>(row, col); //获取通道的像素值（单）dst.at<uchar>(row, col) = cv::saturate_cast<uchar>(v * alpha + beta); //修改通道的像素值（单）//saturate_cast<uchar>：主要是为了防止颜色溢出操作。如果color<0，则color等于0；如果color>255，则color等于255。}}}return dst;
}//--------------------------------------------------------------------------------
// 饱和度
cv::Mat Saturation(cv::Mat src, int saturation)
{float Increment = saturation * 1.0f / 100;cv::Mat temp = src.clone();int row = src.rows;int col = src.cols;for (int i = 0; i < row; ++i){uchar *t = temp.ptr<uchar>(i);uchar *s = src.ptr<uchar>(i);for (int j = 0; j < col; ++j){uchar b = s[3 * j];uchar g = s[3 * j + 1];uchar r = s[3 * j + 2];float max = max3(r, g, b);float min = min3(r, g, b);float delta, value;float L, S, alpha;delta = (max - min) / 255;if (delta == 0)continue;value = (max + min) / 255;L = value / 2;if (L < 0.5)S = delta / value;elseS = delta / (2 - value);if (Increment >= 0){if ((Increment + S) >= 1)alpha = S;elsealpha = 1 - Increment;alpha = 1 / alpha - 1;t[3 * j + 2] =static_cast<uchar>( r + (r - L * 255) * alpha);t[3 * j + 1] = static_cast<uchar>(g + (g - L * 255) * alpha);t[3 * j] = static_cast<uchar>(b + (b - L * 255) * alpha);}else{alpha = Increment;t[3 * j + 2] = static_cast<uchar>(L * 255 + (r - L * 255) * (1 + alpha));t[3 * j + 1] = static_cast<uchar>(L * 255 + (g - L * 255) * (1 + alpha));t[3 * j] = static_cast<uchar>(L * 255 + (b - L * 255) * (1 + alpha));}}}return temp;
}//--------------------------------------------------------------------------------
// 高光
cv::Mat HighLight(cv::Mat src, int highlight)
{// 生成灰度图cv::Mat gray = cv::Mat::zeros(src.size(), CV_32FC1);cv::Mat f = src.clone();f.convertTo(f, CV_32FC3);std::vector<cv::Mat> pics;split(f, pics);gray = 0.299f*pics[2] + 0.587*pics[2] + 0.114*pics[0];gray = gray / 255.f;// 确定高光区cv::Mat thresh = cv::Mat::zeros(gray.size(), gray.type());thresh = gray.mul(gray);// 取平均值作为阈值cv::Scalar t = mean(thresh);cv::Mat mask = cv::Mat::zeros(gray.size(), CV_8UC1);mask.setTo(255, thresh >= t[0]);// 参数设置int max = 4;float bright = highlight / 100.0f / max;float mid = 1.0f + max * bright;// 边缘平滑过渡cv::Mat midrate = cv::Mat::zeros(src.size(), CV_32FC1);cv::Mat brightrate = cv::Mat::zeros(src.size(), CV_32FC1);for (int i = 0; i < src.rows; ++i){uchar *m = mask.ptr<uchar>(i);float *th = thresh.ptr<float>(i);float *mi = midrate.ptr<float>(i);float *br = brightrate.ptr<float>(i);for (int j = 0; j < src.cols; ++j){if (m[j] == 255){mi[j] = mid;br[j] = bright;}else {mi[j] = (mid - 1.0f) / t[0] * th[j] + 1.0f;br[j] = (1.0f / t[0] * th[j])*bright;}}}// 高光提亮，获取结果图cv::Mat result = cv::Mat::zeros(src.size(), src.type());for (int i = 0; i < src.rows; ++i){float *mi = midrate.ptr<float>(i);float *br = brightrate.ptr<float>(i);uchar *in = src.ptr<uchar>(i);uchar *r = result.ptr<uchar>(i);for (int j = 0; j < src.cols; ++j){for (int k = 0; k < 3; ++k){float temp = pow(float(in[3 * j + k]) / 255.f, 1.0f / mi[j])*(1.0 / (1 - br[j]));if (temp > 1.0f)temp = 1.0f;if (temp < 0.0f)temp = 0.0f;uchar utemp = uchar(255*temp);r[3 * j + k] = utemp;}}}return result;
}//--------------------------------------------------------------------------------
// 暖色调
cv::Mat ColorTemperature(cv::Mat src, int warm)
{cv::Mat result = src.clone();int row = src.rows;int col = src.cols;int level = warm/2;for (int i = 0; i < row; ++i){uchar* a = src.ptr<uchar>(i);uchar* r = result.ptr<uchar>(i);for (int j = 0; j < col; ++j){int R,G,B;// R通道R = a[j * 3 + 2];R = R + level;if (R > 255) {r[j * 3 + 2] = 255;}else if (R < 0) {r[j * 3 + 2] = 0;}else {r[j * 3 + 2] = R;}// G通道G = a[j * 3 + 1];G = G + level;if (G > 255) {r[j * 3 + 1] = 255;}else if (G < 0) {r[j * 3 + 1] = 0;}else {r[j * 3 + 1] = G;}// B通道B = a[j * 3];B = B - level;if (B > 255) {r[j * 3] = 255;}else if (B < 0) {r[j * 3] = 0;}else {r[j * 3] = B;}}}return result;
}//--------------------------------------------------------------------------------
// 阴影
cv::Mat Shadow(cv::Mat src, int shadow)
{// 生成灰度图cv::Mat gray = cv::Mat::zeros(src.size(), CV_32FC1);cv::Mat f = src.clone();f.convertTo(f, CV_32FC3);std::vector<cv::Mat> pics;split(f, pics);gray = 0.299f*pics[2] + 0.587*pics[2] + 0.114*pics[0];gray = gray / 255.f;// 确定阴影区cv::Mat thresh = cv::Mat::zeros(gray.size(), gray.type()); thresh = (1.0f - gray).mul(1.0f - gray);// 取平均值作为阈值cv::Scalar t = mean(thresh);cv::Mat mask = cv::Mat::zeros(gray.size(), CV_8UC1);mask.setTo(255, thresh >= t[0]);// 参数设置int max = 4;float bright = shadow / 100.0f / max;float mid = 1.0f + max * bright;// 边缘平滑过渡cv::Mat midrate = cv::Mat::zeros(src.size(), CV_32FC1);cv::Mat brightrate = cv::Mat::zeros(src.size(), CV_32FC1);for (int i = 0; i < src.rows; ++i){uchar *m = mask.ptr<uchar>(i);float *th = thresh.ptr<float>(i);float *mi = midrate.ptr<float>(i);float *br = brightrate.ptr<float>(i);for (int j = 0; j < src.cols; ++j){if (m[j] == 255){mi[j] = mid;br[j] = bright;}else {mi[j] = (mid - 1.0f) / t[0] * th[j]+ 1.0f; br[j] = (1.0f / t[0] * th[j])*bright; }}}// 阴影提亮，获取结果图cv::Mat result = cv::Mat::zeros(src.size(), src.type());for (int i = 0; i < src.rows; ++i){float *mi = midrate.ptr<float>(i);float *br = brightrate.ptr<float>(i);uchar *in = src.ptr<uchar>(i);uchar *r = result.ptr<uchar>(i);for (int j = 0; j < src.cols; ++j){for (int k = 0; k < 3; ++k){float temp = pow(float(in[3 * j + k]) / 255.f, 1.0f / mi[j])*(1.0 / (1 - br[j]));if (temp > 1.0f)temp = 1.0f;if (temp < 0.0f)temp = 0.0f;uchar utemp = uchar(255*temp);r[3 * j + k] = utemp;}}}return result;
}//--------------------------------------------------------------------------------
// 漫画效果
cv::Mat Cartoon(cv::Mat src, double clevel, int d, double sigma, int size)
{//（1）中值滤波cv::Mat m;cv::medianBlur(src, m, 7);//（2）提取轮廓cv::Mat c;clevel = cv::max(40., cv::min(80., clevel));cv::Canny(m, c, clevel, clevel *3);//（3）轮廓膨胀cv::Mat k = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(2, 2));cv::dilate(c, c, k);//（4）图像反转c = c / 255;c = 1 - c;//（5）均值滤波cv::Mat cf;c.convertTo(cf, CV_32FC1); // 类型转换 cv::blur(cf, cf, cv::Size(5, 5)); //（6）双边滤波cv::Mat srcb;d = cv::max(0, cv::min(10, d));sigma = cv::max(10., cv::min(250., sigma));cv::bilateralFilter(src, srcb, d, sigma, sigma);size = cv::max(10, cv::min(25, size));cv::Mat temp = srcb / size;temp = temp * size;//（7）通道合并cv::Mat c3;cv::Mat cannyChannels[] = { cf, cf, cf };cv::merge(cannyChannels, 3, c3);//（8）图像相乘cv::Mat tempf;temp.convertTo(tempf, CV_32FC3); // 类型转换cv::multiply(tempf, c3, tempf); tempf.convertTo(temp, CV_8UC3); // 类型转换return temp;
}//--------------------------------------------------------------------------------
// 白平衡-灰度世界
cv::Mat WhiteBalcane_Gray(cv::Mat src)
{//（1）3通道处理cv::Mat result = src.clone();if (src.channels() != 3){std::cout << "The number of image channels is not 3." << std::endl;return result;}//（2）通道分离std::vector<cv::Mat> Channel;cv::split(src, Channel);//（3）计算通道灰度值均值double Bm = cv::mean(Channel[0])[0];double Gm = cv::mean(Channel[1])[0];double Rm = cv::mean(Channel[2])[0];double Km = (Bm + Gm + Rm) / 3;//（4）通道灰度值调整Channel[0] *= Km / Bm;Channel[1] *= Km / Gm;Channel[2] *= Km / Rm;//（5）通道合并cv::merge(Channel, result);return result;
}//--------------------------------------------------------------------------------
// 白平衡-完美反射
cv::Mat WhiteBalcane_PRA(cv::Mat src)
{//（1）3通道处理cv::Mat result = src.clone();if (src.channels() != 3){std::cout << "The number of image channels is not 3." << std::endl;return result;}//（2）通道分离std::vector<cv::Mat> Channel;cv::split(src, Channel);//（3）计算单通道最大值int row = src.rows;int col = src.cols;int RGBSum[766] = { 0 };uchar maxR, maxG, maxB;for (int i = 0; i < row; ++i){uchar *b = Channel[0].ptr<uchar>(i);uchar *g = Channel[1].ptr<uchar>(i);uchar *r = Channel[2].ptr<uchar>(i);for (int j = 0; j < col; ++j){int sum = b[j] + g[j] + r[j];RGBSum[sum]++;maxB = cv::max(maxB, b[j]);maxG = cv::max(maxG, g[j]);maxR = cv::max(maxR, r[j]);}}//（4）计算最亮区间下限Tint T = 0;int num = 0;int K = static_cast<int>(row * col * 0.1);for (int i = 765; i >= 0; --i){num += RGBSum[i];if (num > K){T = i;break;}}//（5）计算单通道亮区平均值double Bm = 0.0, Gm = 0.0, Rm = 0.0;int count = 0;for (int i = 0; i < row; ++i){uchar *b = Channel[0].ptr<uchar>(i);uchar *g = Channel[1].ptr<uchar>(i);uchar *r = Channel[2].ptr<uchar>(i);for (int j = 0; j < col; ++j){int sum = b[j] + g[j] + r[j];if (sum > T){Bm += b[j];Gm += g[j];Rm += r[j];count++;}}}Bm /= count;Gm /= count;Rm /= count;//（6）通道调整Channel[0] *= maxB / Bm;Channel[1] *= maxG / Gm;Channel[2] *= maxR / Rm;//（7）通道合并cv::merge(Channel, result);return result;
}//--------------------------------------------------------------------------------
// 浮雕
cv::Mat Relief(cv::Mat src)
{CV_Assert(src.channels() == 3);int row = src.rows;int col = src.cols;cv::Mat temp = src.clone();for (int i = 1; i < row-1; ++i){uchar *s1 = src.ptr<uchar>(i - 1);uchar *s2 = src.ptr<uchar>(i + 1);uchar *t = temp.ptr<uchar>(i);for (int j = 1; j < col-1; ++j){for (int k = 0; k < 3; ++k){int RGB = s1[3 * (j - 1) + k] - s2[3 * (j + 1) + k] + 128;if (RGB < 0)RGB = 0;if (RGB > 255)RGB = 255;t[3*j+k] =(uchar)RGB;}}}return temp;
}//--------------------------------------------------------------------------------
// 羽化
cv::Mat Eclosion(cv::Mat src, cv::Point center, float level)
{if (level > 0.9)level = 0.9f;float diff = (1-level) * (src.rows / 2 * src.rows / 2 + src.cols / 2 * src.cols / 2);cv::Mat result = src.clone();for (int i = 0; i < result.rows; ++i){for (int j = 0; j < result.cols; ++j){float dx = float(center.x - j);float dy = float(center.y - i);float ra = dx * dx + dy * dy;float m = ((ra-diff) / diff * 255)>0? ((ra - diff) / diff * 255):0;int b = result.at<cv::Vec3b>(i, j)[0];int g = result.at<cv::Vec3b>(i, j)[1];int r = result.at<cv::Vec3b>(i, j)[2];b = (int)(b+ m);g = (int)(g + m);r = (int)(r + m);result.at<cv::Vec3b>(i, j)[0] = (b > 255 ? 255 : (b < 0 ? 0 : b));result.at<cv::Vec3b>(i, j)[1] = (g > 255 ? 255 : (g < 0 ? 0 : g));result.at<cv::Vec3b>(i, j)[2] = (r > 255 ? 255 : (r < 0 ? 0 : r));}}return result;
}//--------------------------------------------------------------------------------
// 锐化
cv::Mat Sharpen(cv::Mat input, int percent, int type)
{cv::Mat result;cv::Mat s = input.clone();cv::Mat kernel;switch (type){case 0:kernel = (cv::Mat_<int>(3, 3) <<0, -1, 0,-1, 4, -1,0, -1, 0);case 1:kernel = (cv::Mat_<int>(3, 3) <<-1, -1, -1,-1, 8, -1,-1, -1, -1);default:kernel = (cv::Mat_<int>(3, 3) <<0, -1, 0,-1, 4, -1,0, -1, 0);}cv::filter2D(s, s, s.depth(), kernel);result = input + s * 0.01 * percent;return result;
}//--------------------------------------------------------------------------------
// 颗粒感
cv::Mat Grainy(cv::Mat src, int level)
{int row = src.rows;int col = src.cols;if (level > 100)level = 100;if (level < 0)level = 0;cv::Mat result = src.clone();for (int i = 0; i < row; ++i){uchar *t = result.ptr<uchar>(i);for (int j = 0; j < col; ++j){for (int k = 0; k < 3; ++k){int temp = t[3 * j + k];temp += ((rand() % (2 * level)) - level);if (temp < 0)temp = 0;if (temp > 255)temp = 255;t[3 * j + k] = temp;}}}return result;
}
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