Question

我有大量的图片，我已将其细分为片段，使得它们的矩阵看起来像：

img = [ 1 1 1 1 1 2 2 2 3 3 3 3  
        1 1 1 1 2 2 2 2 2 3 3 3  
        1 1 1 4 4 4 2 2 2 3 3 3  
        5 5 5 5 5 5 5 2 2 3 3 3 ];

其中每个数字代表不同的区域，每个区域是任意形状的。所以在这种情况下，区域1有邻居2,4和5，区域2有邻居1,3和4，依此类推。

我已将所有区域提取到单独的单元格中并获得统计数据（均值，方差等），我计划将其用于合并具有特定容差范围内的统计数据的区域。我正在努力想出一种有效的方法来获得每个地区的邻居，以允许合并发生。

我有一个可怕的解决方案，即使只有一张图片需要很长时间：

referenceImage = [ 1 1 1 1 1 2 2 2 3 3 3 3;
                    1 1 1 1 2 2 2 2 2 3 3 3;
                    1 1 1 4 4 4 2 2 2 3 3 3;
                    5 5 5 5 5 5 5 2 2 3 3 3];

% Wish to extract each region into a separate cell
lastSP = 5;
sps = 1:lastSP;
% Could be a way to vectorise the below loop but it escapes me
superPixels(lastSP) = struct('Indices', 0, 'Neighbours', 0);
% Split data into separate cells
parfor a = 1 : lastSP
    inds = find(referenceImage == sps(a));
    superPixels(a).Indices = inds;
end

szs = size(referenceImage); % Sizes of RGB Image
for a = 1 : lastSP + 1
    mask = zeros(szs(1), szs(2)); % Just bin mask wanted
    mask(superPixels(a).Indices) = 1; % Mark the region pixels as one
    mask = xor(bwmorph(mask, 'thicken'), mask); % Obtain the outlying regions

    inds = find(mask ==1); % Fetch the external region indices

    neighbours = []; % Have to dynamically grow neighbours matrix
    neigh = 1;  

    for b = 1 : length(inds)
        found = false;
        if ~isempty(neighbours) % Check neighbours first
            for c = 1 : length(neighbours)
                if any(superPixels(neighbours(c)).Indices == inds(b))
                    found = true;
                    break;
                end
            end
        end

        if ~found
           for c = 1 : lastSP + 1 % Check every other region
               if any(superPixels(c).Indices == inds(b))
                    neighbours(neigh) = c;
                    neigh = neigh + 1;
                    break;
                end
           end
        end            
    end  
    superPixels(a).Neighbours = neighbours;
end

我想知道这是否是解决此问题的最佳方法。我知道最后一个循环是主要的问题，但我不能想出另一种合理写这个的方法，除非我递归并检查已知邻居的邻居。

非常感谢任何正确方向的帮助或推动;谢谢！

Answer 1

一个简单的（但可能不是最有效的）解决方案是扩展每个区域掩码以挑选邻居：

labels = unique(img);
nLabels = length(labels);
neighbors = cell(nLabels,1);

for iLabel = 1:nLabels
   msk = img == labels(iLabel);
   adjacentPixelMask = imdilate(msk,true(3)) & ~msk;
   neighbors{iLabel} = unique(img(adjacentPixelMask));
end

neighbors{1}
ans =
     2
     4
     5

Matlab：矩阵邻居提取

1 个答案: