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標題: MMBEBHE代碼及逐行講解 [打印本頁]

作者: aceamber 時間: 2024-6-24 01:16
標題: MMBEBHE代碼及逐行講解
input_image = imread('圖片地址.tif');
% Step 1 計算每個閾值級別的 AMBE
hist = imhist(input_image);  % 計算直方圖
total_pixels = numel(input_image);% 獲取圖像中的總像素數n
ambe_values = zeros(256, 1); % 初始化數組以便儲存AMBE的值

% 根據閾值將輸入的直方圖一分為二
      for threshold =[]
         lower_hist = hist(1:threshold + 1);
         upper_hist = hist(threshold + 2:end);

   % 檢查是否有任何直方圖為空
         if isempty(lower_hist) || isempty(upper_hist)
            ambe_values(threshold + 1) = inf; %將AMBE設置為無限大
         else
            lower_cdf = cumsum(lower_hist);
            upper_cdf = cumsum(upper_hist);% 計算nk

            % 按像素總數歸一化Pr（rk）=nk/n
            lower_cdf_normalized = lower_cdf / total_pixels;
            upper_cdf_normalized = upper_cdf / total_pixels;

            % 計算兩個區域的平均強度
            mean_lower = sum((0:threshold) .* lower_hist) / sum(lower_hist);
            mean_upper = sum((threshold + 1:255) .* upper_hist) / sum(upper_hist);

            % 計算絕對平均亮度誤差（AMBE）
            ambe_values(threshold + 1) = abs(mean_upper - mean_lower);
         end
      end

% STEP 2 找到產生最小 MBE 的閾值水平 XT
[~, optimal_threshold] = min(ambe_values);
XT = optimal_threshold - 1;

% Step 3 根據找到的 XT將輸入直方圖一分為二，獨立均衡化
% 根據最佳閾值分割圖像
lower_region = input_image <= XT;
upper_region = input_image > XT;

% 兩個區域單獨直方圖均衡化
lower_eq = histeq(input_image(lower_region), 256);
upper_eq = histeq(input_image(upper_region), 256);

% 合并兩個均衡化區域得出最終結果
result_image = input_image;
result_image(lower_region) = lower_eq;
result_image(upper_region) = upper_eq;

% 顯示最終圖像&直方圖
figure
imshow(input_image)
title('原圖像');
figure
imshow(result_image)
title('圖像MMBEBHE的結果');
figure
imhist(input_image);
title('原圖像的直方圖');
figure
imhist(result_image);
title('圖像MMBEBHE的直方圖')

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