水下成像模型分离背景光， 并用retinex算法增强 matlab代码如何编写

实现水下成像模型分离背景光并用retinex算法增强可以按照以下步骤进行：

1. 读取水下成像图像

img = imread('underwater_image.jpg');

2. 分离背景光

% 转换成灰度图像
gray_img = rgb2gray(img);

% 计算灰度图像的梯度
[dx, dy] = gradient(double(gray_img));

% 计算梯度的幅值
grad_mag = sqrt(dx.^2 + dy.^2);

% 计算背景光的平均值
mean_grad_mag = mean(grad_mag(:));

% 分离背景光
background = gray_img;
background(grad_mag < mean_grad_mag) = 0;

3. 进行retinex算法增强

% 设置参数
alpha = 125;
beta = 46;
low_cutoff = 50;
high_cutoff = 180;

% 进行单尺度Retinex增强
log_img = log(double(background) + 1);
log_img_fft = fft2(log_img);
lpf = fspecial('gaussian', size(background), alpha);
lpf_fft = fft2(lpf, size(background, 1), size(background, 2));
log_img_filtered = real(ifft2(log_img_fft .* lpf_fft));
rescaled_log_img = (255 / (max(log_img_filtered(:)) - min(log_img_filtered(:)))) * (log_img_filtered - min(log_img_filtered(:)));
single_scale_retinex = exp(rescaled_log_img) - 1;

% 进行多尺度Retinex增强
msr = zeros(size(background));
for sigma = low_cutoff:beta:high_cutoff
    lpf = fspecial('gaussian', size(background), sigma);
    lpf_fft = fft2(lpf, size(background, 1), size(background, 2));
    msr = msr + real(ifft2(log_img_fft .* lpf_fft));
end
msr = msr ./ (floor((high_cutoff - low_cutoff) / beta) + 1);
msr = (255 / (max(msr(:)) - min(msr(:)))) * (msr - min(msr(:)));
multi_scale_retinex = exp(msr) - 1;

% 进行自适应增强
k = 0.04;
sigma = 10;
edge_map = edge(gray_img, 'canny', k, sigma);
adaptive_retinex = single_scale_retinex .* edge_map + multi_scale_retinex .* (1 - edge_map);

% 显示结果
figure;
subplot(2, 2, 1);
imshow(img);
title('Original image');
subplot(2, 2, 2);
imshow(background);
title('Background');
subplot(2, 2, 3);
imshow(single_scale_retinex);
title('Single-scale retinex enhancement');
subplot(2, 2, 4);
imshow(adaptive_retinex);
title('Adaptive retinex enhancement');

这样就可以实现水下成像模型分离背景光并用retinex算法增强了。