对背景光进行Retinex增强结合白平衡一起 matlab代码怎么写

Retinex增强算法是一种经典的图像增强算法，可以有效地恢复图像的亮度和对比度。在此基础上，结合白平衡算法可以进一步提高图像的色彩还原度。下面是一份Matlab代码，实现了背景光进行Retinex增强结合白平衡的功能：

clc;
clear all;
close all;
 
% 读取原始图像
img = imread('image.jpg');
figure;
imshow(img);
title('Original Image');
 
% Retinex增强算法
img_retinex = zeros(size(img));
for i = 1:3
    img_retinex(:,:,i) = retinex_enhancement(img(:,:,i));
end
figure;
imshow(uint8(img_retinex));
title('Retinex Enhanced Image');
 
% 白平衡算法
img_wb = white_balance(img_retinex);
figure;
imshow(uint8(img_wb));
title('White Balanced Image');
 
% Retinex增强结合白平衡
img_retinex_wb = zeros(size(img));
for i = 1:3
    img_retinex_wb(:,:,i) = retinex_enhancement(img_wb(:,:,i));
end
figure;
imshow(uint8(img_retinex_wb));
title('Retinex Enhanced and White Balanced Image');
 
% Retinex增强函数
function img_retinex = retinex_enhancement(img)
    img_log = log(double(img) + 1);
    mu = mean2(img_log);
    sigma = std2(img_log);
    img_retinex = (img_log - mu) / (sigma + 0.001);
    img_retinex = exp(img_retinex) - 1;
    img_retinex = img_retinex / max(img_retinex(:)) * 255;
end
 
% 白平衡函数
function img_wb = white_balance(img)
    R = img(:,:,1);
    G = img(:,:,2);
    B = img(:,:,3);
    K = (mean2(R) + mean2(G) + mean2(B)) / 3;
    Kr = K / mean2(R);
    Kg = K / mean2(G);
    Kb = K / mean2(B);
    img_wb(:,:,1) = R * Kr;
    img_wb(:,:,2) = G * Kg;
    img_wb(:,:,3) = B * Kb;
end

其中，`retinex_enhancement`函数实现了Retinex增强算法，`white_balance`函数实现了白平衡算法。在主函数中，先对原始图像进行Retinex增强，然后进行白平衡处理，最后再对白平衡后的图像进行Retinex增强。最终得到的`img_retinex_wb`即为背景光进行Retinex增强结合白平衡后的图像。