照片美化

#include
using namespace cv;
using namespace std;
Mat meibai(Mat &img);
Mat wImg(Mat &img1, Mat &img2);
void lbImg(Mat &img1, Mat &img2, Mat &result, int rad, int e);
void dealImg(Mat &img);

int main() {
	Mat img = imread("E://图片//色斑.jpg");
	if (img.empty()) {
		return -1;
	}

	imshow("img_org", img);
	dealImg(img);

	waitKey(0);
	destroyAllWindows;
	return 0;
}
void dealImg(Mat &img) {
	Mat tem = img.clone();
	Mat result = img.clone();

	Mat gray;
	cvtColor(img, gray, CV_BGR2GRAY);
	vector channelsone, channelstwo;
	split(tem, channelsone);
	split(result, channelstwo);
	for (int i = 0; i < 3; i++) {
		lbImg(channelsone[i], gray, channelstwo[i], 18, 500);
	}
	merge(channelstwo, result);
	result = wImg(result, img);
	imshow("result", result);
}

void lbImg(Mat &img1, Mat &img2, Mat &result, int rad, int e) {

	img1.convertTo(img1, CV_32F);
	img2.convertTo(img2, CV_32F);
	result.convertTo(result, CV_32F);

	Mat tem_img1, tem_img2;
	multiply(img1, img2, tem_img1);
	multiply(img2, img2, tem_img2);  //求方差用

	Size dealSize(rad, rad);

	Mat box1, box2, box3, box4;
	boxFilter(tem_img1, box1, CV_32F, dealSize);    //两图像的均值乘积
	boxFilter(tem_img2, box2, CV_32F, dealSize);    //平方的均值

	boxFilter(img1, box3, CV_32F, dealSize);   //图片1的均值
	boxFilter(img2, box4, CV_32F, dealSize);    //图片2的均值
	
	Mat one, two, a, b;
	one = box1 - box4.mul(box3);   //分子
	two = box2 - box4.mul(box4) + e;
	divide(one, two, a);   //得到系数
	b = box3 - a.mul(box4);   //得到常数

	Mat box_r1, box_r2;
	boxFilter(a, box_r1, CV_32F, dealSize);
	boxFilter(b, box_r2, CV_32F, dealSize);

	result = box_r1.mul(img2) + box_r2;
	result.convertTo(result, CV_8U);
}
Mat wImg(Mat &img1, Mat &img2) {
	Mat y = img1.clone();
	int alpha = 30;
	//img1 = (y*(100 - alpha) + (y + 2 * img1 - 256)*alpha) / 100;  //与原图混合
	for (int i = 0; i < img1.rows; i++) {   //羽化融合,也可锐化操作增加纹理
		uchar * p1 = img1.ptr(i);
		uchar * p2 = img2.ptr(i);
		for (int j = 0; j < img1.cols; j++) {
			p1[j * 3 + 0] = (p2[j * 3 + 0] * alpha + (255 - alpha) * p1[j * 3 + 0]) >> 8;
			p1[j * 3 + 1] = (p2[j * 3 + 1] * alpha + (255 - alpha) * p1[j * 3 + 1]) >> 8;
			p1[j * 3 + 2] = (p2[j * 3 + 2] * alpha + (255 - alpha) * p1[j * 3 + 2]) >> 8;
		}
	}
	img1 = meibai(img1);   //美白
	return img1;
}
Mat meibai(Mat &img) {

	Mat tem = img.clone();
	tem.convertTo(tem, CV_32F, 1/255.0);
	Mat result(tem.size(), tem.type());
	
	float beta = 4.0;
	for (int i = 0; i < img.rows; i++) {
		float *p1 = tem.ptr(i);
		float *p2 = result.ptr(i);
		for (int j = 0; j < img.cols; j++) {
			float Bt = log(p1[j * 3 + 0] * (beta - 1) + 1);
			float Gt = log(p1[j * 3 + 1] * (beta - 1) + 1);
			float Rt = log(p1[j * 3 + 2] * (beta - 1) + 1);
			p2[j * 3 + 0] = Bt / log(beta);
			p2[j * 3 + 1] = Gt / log(beta);
			p2[j * 3 + 2] = Rt / log(beta);
		}
	}
	result.convertTo(result, CV_8U, 255);
	
	return result;
}

效果：

笔记：