MATLAB代码，对灰度图像进行OSTU二值化

以下是MATLAB代码，对灰度图像进行OSTU二值化：

% 读取灰度图像
img = imread('gray_image.png');

% 计算图像的直方图
histogram = imhist(img);

% 获取图像像素总数
total_pixels = numel(img);

% 初始化最优阈值和最大类间方差
optimal_threshold = 0;
max_variance = 0;

% 对每个灰度级别进行遍历，计算每个灰度级别作为阈值时的类间方差
for threshold = 1:255
    % 计算前景和背景像素的数量
    foreground_pixels = sum(histogram(threshold+1:256));
    background_pixels = sum(histogram(1:threshold));
    
    % 计算前景和背景像素的概率
    foreground_probability = foreground_pixels / total_pixels;
    background_probability = background_pixels / total_pixels;
    
    % 计算前景和背景像素的平均灰度值
    foreground_mean = sum((threshold+1:256) .* histogram(threshold+1:256)) / foreground_pixels;
    background_mean = sum((1:threshold) .* histogram(1:threshold)) / background_pixels;
    
    % 计算类间方差
    variance = foreground_probability * background_probability * (foreground_mean - background_mean)^2;
    
    % 更新最优阈值和最大类间方差
    if variance > max_variance
        max_variance = variance;
        optimal_threshold = threshold;
    end
end

% 二值化图像
binary_img = imbinarize(img, optimal_threshold/255);

% 显示原始图像和二值化图像
figure;
subplot(1,2,1);
imshow(img);
title('Original Image');
subplot(1,2,2);
imshow(binary_img);
title('OSTU Binarized Image');