matlab碎纸片的拼接复原代码

碎纸片拼接复原是一个有趣的图像处理问题。下面是一个使用MATLAB实现的简单代码示例：

% 读入碎片图像
folder = 'path/to/fragment/images';
filelist = dir(fullfile(folder, '*.jpg')); % 根据实际情况修改图片格式
num_files = length(filelist);

% 创建一个空白画布
canvas = zeros(3000, 3000, 3); % 根据实际情况设置画布大小和通道数

% 随机选取一张图像作为起点
start_idx = randi(num_files);
start_image = imread(fullfile(folder, filelist(start_idx).name));

% 将起点图像放置在画布中央
canvas_size = size(canvas);
start_size = size(start_image);
canvas((canvas_size(1)-start_size(1))/2+1:(canvas_size(1)+start_size(1))/2, ...
       (canvas_size(2)-start_size(2))/2+1:(canvas_size(2)+start_size(2))/2, :) = start_image;

% 删除已使用的图像
filelist(start_idx) = [];

% 每次随机选取一张图像与画布边缘最接近的位置进行拼接
while ~isempty(filelist)
    min_distance = inf;
    min_idx = 0;
    for i = 1:length(filelist)
        image = imread(fullfile(folder, filelist(i).name));
        for j = 1:4 % 遍历图像的四个边缘
            edge = image(1,:,j); % 取出边缘
            if all(edge == 0) % 边缘为黑色，则说明该边缘与其他碎片不相连
                continue;
            end
            % 计算该边缘与画布边缘的欧氏距离
            distances = sqrt(sum((edge - reshape(canvas(:,1,j), [], 1)).^2, 2));
            min_distance_edge = min(distances);
            if min_distance_edge < min_distance
                min_distance = min_distance_edge;
                min_idx = i;
                % 记录该碎片应该放置在画布的哪个边缘
                min_edge = j;
            end
        end
    end
    % 将选中的碎片放置在画布上
    image = imread(fullfile(folder, filelist(min_idx).name));
    canvas = place_image(canvas, image, min_edge, min_distance);
    % 删除已使用的图像
    filelist(min_idx) = [];
end

% 显示拼接结果
imshow(uint8(canvas));

其中的 `place_image` 函数用于将一张图像放置在画布上，具体实现如下：

function new_canvas = place_image(canvas, image, edge, distance)
% edge 指定了碎片应该放置在画布的哪个边缘，取值范围为 1~4，分别表示上、右、下、左
% distance 指定了碎片应该放置在画布上距离最近的位置

% 将 image 旋转 0/90/180/270 度，使其边缘与 edge 指定的边缘对齐
if edge == 1 % 上边缘
    image = imrotate(image, 90);
elseif edge == 2 % 右边缘
    image = imrotate(image, 180);
elseif edge == 3 % 下边缘
    image = imrotate(image, 270);
end

% 将 image 粘贴到画布上
image_size = size(image);
canvas_size = size(canvas);
if edge == 1 % 上边缘
    new_canvas = [image; canvas(1:distance-image_size(1), :, :); canvas(distance:end, :, :)];
elseif edge == 2 % 右边缘
    new_canvas = [canvas(:, 1:distance-image_size(2), :), image, canvas(:, distance:end, :)];
elseif edge == 3 % 下边缘
    new_canvas = [canvas(1:distance-image_size(1), :, :); canvas(distance:end, :, :); image];
elseif edge == 4 % 左边缘
    new_canvas = [canvas(:, distance:end, :), image, canvas(:, 1:distance-image_size(2), :)];
end
end

注意：这个代码示例只是一个简单的实现，可能无法处理复杂的场景。如果需要更高的准确性和可靠性，需要更加复杂的算法和代码实现。