MATLAB: Index information for conv2(.,.)

digital signal processingimage processing

I have an image X (dimension N1xN2) and a filter Y(dimension 3×5). I can use matlab command conv2(X,Y) to get the filtered image Z. Now I want to get another matrix Z_Index of dimension (N1N2 x 15). The kth row of Z_index(k,:) should contain linear index information of those x's that contributed in kth element of Z. How can I get such a matrix?

Best Answer

One possible way:

indices = reshape(1:numel(X), size(X));
usedindices = nlfilter(indices, size(Y), @(idx) {idx(:)});
Z = [usedindices{:}]'

You get 0 for those k indices near the edges due to the zero padding.

Related Solutions

MATLAB: Map a function over specific dimensions of matrix

You would have to modify your function F like this to achieve what I think you want:

      function fct = F(Ai)
          % We first take the subscript associated to the number Ai
          b_dim=numel(size_M(1:end-k)); 
          subscripts=cell(1, b_dim);
          % We take the indices corresponding to Ai
          [subscripts{:}]=ind2sub(size_M(1:end-k),Ai);
          % replicate individual indices to the size of the k-dimensional submatrices
          size_k = size_M(end-k+1:end);
          subscripts = cellfun(@(idx) repmat(idx, size_k), subscripts, 'UniformOutput', false);
          % emulate colon for the remaining dimension by explicitly listing all indices
          k_subscripts = arrayfun(@(sz) 1:sz, size_k, 'UniformOutput', false);
          [k_subscripts{:}] = ndgrid(k_subscripts{:});
          % convert subscripts to linear indices and index
          M_k = M(sub2ind(size(M), subscripts{:}, k_subscripts{:}));
          % We then apply the function f to the good element of matrix M
          fct=f(M_k);
      end

That is you have to translate your subscripts back to linear indices and explicitly list all the indices for the remaining dimensions instead of an unknown number of colons.

However, yes the whole thing is way overly complicated. You only need to do:

function B = mapping(M, f, k)
   B = cellfun(@(M_k) f(squeeze(M_k)), num2cell(M, k+1:ndims(M)));
end

Alternatively, you could permute the dimensions which would avoid the squeeze in the cellfun (and hence the cost of the anonymous function) but require a squeeze at the end. As permute is expensive, you may not gain anything:

function B = mapping(M, f, k)
   B = squeeze(cellfun(f, num2cell(permute(M, [k+1:ndims(M), 1:k]), 1:k)));
end

MATLAB: Minimum of a 3D matrix

M=rand(2,2,3);
out=min(reshape(min(M),size(M,2),[],1))'

out=arrayfun(@(x) min(min(M(:,:,x))),1:size(M,3))'

If you want to get the corresponding index

M=rand(6,4,5);
[n,m,p]=size(M)
[c,idx]=min(M)
[c1,idx2]=min(c)
idx1=arrayfun(@(x) idx(1,idx2(1,1,x),x),(1:p)') 
v=[c1(:) idx1(:) idx2(:) (1:p)' ]

Best Answer

Related Solutions

MATLAB: Map a function over specific dimensions of matrix

MATLAB: Minimum of a 3D matrix

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