#include<opencv2/opencv.hpp>
using namespace cv;
using namespace std;
cv::Mat GW(const cv::Mat srcImage)
{
int beta;//美白系数
cv::Mat dstImage;
vector<cv::Mat> Channels;
cv::split(srcImage, Channels);
cv::Mat B = Channels[0]; cv::Mat G = Channels[1]; cv::Mat R = Channels[2];
double Baver = cv::mean(B)[0]; double Gaver = cv::mean(G)[0]; double Raver = cv::mean(R)[0];
beta = 2;
double K = (Baver + Gaver + Raver) / beta; //计算增益系数
double Kb, Kg, Kr;
Kb = K / Baver; Kg = K / Gaver; Kr = K / Raver;
//白平衡处理后的通道
cv::Mat dstB, dstG, dstR;
dstB = B * Kb; dstG = G * Kg; dstR = R * Kr;
cout << cv::mean(dstB)[0] << " " << cv::mean(dstG)[0] << " " << cv::mean(dstB)[0] << endl;
vector<cv::Mat> dstChanges;
dstChanges.push_back(dstB); dstChanges.push_back(dstG); dstChanges.push_back(dstR);
cv::merge(dstChanges, dstImage);//合并通道
return dstImage;
}
int main()
{
cv::Mat src = cv::imread("G:\\12.png");
cv::Mat dst = GW(src);
cv::imshow("dst", dst);
cv::imshow("src", src);
cv::waitKey(0);
system("pause");
return 0;
}
import cv2
import numpy as np
def GW(orgImg):
B, G, R = np.double(orgImg[:, :, 0]), np.double(orgImg[:, :, 1]), np.double(orgImg[:, :, 2])
B_ave, G_ave, R_ave = np.mean(B),np.mean(G),np.mean(R)
K = (B_ave + G_ave + R_ave) / 3
Kb,Kg,Kr = K/B_ave,K/G_ave,K/R_ave
Ba = (B * Kb)
Ga = (G * Kg)
Ra = (R * Kr)
print(np.mean(Ba),np.mean(Ga),np.mean(Ra))
dst_img = np.uint8(np.zeros_like(orgImg))
dst_img[:, :, 0] = Ba
dst_img[:, :, 1] = Ga
dst_img[:, :, 2] = Ra
cv2.imshow("dstimg", dst_img)
cv2.waitKey(0)
if __name__ == '__main__':
orgImg = cv2.imread("E:\Py3.6_Proje\AWB\img3.jpg")
cv2.imshow("orgImg",orgImg)
cv2.waitKey(0)
GW(orgImg)
