下列函数都是怎样运行的，将源代码展示出来：I = imread('瑕疵图像.png'); I_gray = rgb2gray(I); sigma = 1; kernel_size = 3; I_blurred = imgaussfilt(I_gray, sigma, 'FilterSize', kernel_size); threshold_low = 0.1; threshold_high = 0.9; I_edges = edge(I_blurred,'Canny',[threshold_low,threshold_high]); connectivity = 8; CC = bwconncomp(I_edges, connectivity); numPixels = cellfun(@numel, CC.PixelIdxList); [~, idx] = max(numPixels); I_target = false(size(I_edges)); I_target(CC.PixelIdxList{idx}) = true; figure; subplot(1,2,1); imshow(I); title('原始图像'); subplot(1,2,2); imshow(I_target); title('提取结果');

以下是代码展示：

I = imread('瑕疵图像.png'); % 读入图像
I_gray = rgb2gray(I); % 转换为灰度图像
sigma = 1; kernel_size = 3; % 设置高斯模糊参数
I_blurred = imgaussfilt(I_gray, sigma, 'FilterSize', kernel_size); % 对灰度图像进行高斯模糊
threshold_low = 0.1; threshold_high = 0.9; % 设置Canny边缘检测的阈值
I_edges = edge(I_blurred,'Canny',[threshold_low,threshold_high]); % 对高斯模糊后的灰度图像进行Canny边缘检测
connectivity = 8; % 设置连通域的连接方式
CC = bwconncomp(I_edges, connectivity); % 对边缘检测结果进行连通域分析
numPixels = cellfun(@numel, CC.PixelIdxList); % 获取每个连通域的像素数量
[~, idx] = max(numPixels); % 找到像素数量最多的连通域
I_target = false(size(I_edges)); % 创建和边缘检测结果相同大小的逻辑数组
I_target(CC.PixelIdxList{idx}) = true; % 将像素数量最多的连通域赋值为true
figure; % 创建新的图像窗口
subplot(1,2,1); imshow(I); title('原始图像'); % 显示原始图像
subplot(1,2,2); imshow(I_target); title('提取结果'); % 显示提取结果