getting following error,help to rectify this

      function [Inc Knc] = Nc(I,SI,SX,r,sNcut,sArea)
      %%ncutImageSegment
      [nRow, nCol,c] = size(I);                  % Changes
      N = nRow * nCol;
      V = reshape(I, N, c);                      % connect up-to-down way. Vertices of Graph
      %%ncutComputeW                            
      W = sparse(N,N);                           % Step 1. Compute weight matrix W, and D
      F = reshape(I, N, 1, c);                   % col vector % Spatial Location
      X = cat(3, repmat((1:nRow)', 1, nCol), repmat((1:nCol), nRow, 1));
      X = reshape(X, N, 1, 2);                   % col vector

      for ic=1:nCol                              % Future Work: Reduce computation to half. It can be done because W is symmetric mat
          for ir=1:nRow                          % matlab tricks for fast computation (Avoid 'for' loops as much as possible, instead use repmat.)

              % This range satisfies |X(i) - X(j)| <= r (block distance)
              jc = (ic - floor(r)) : (ic + floor(r)); % vector
              jr = ((ir - floor(r)) :(ir + floor(r)))';
              jc = jc(jc >= 1 & jc <= nCol);
              jr = jr(jr >= 1 & jr <= nRow);
              jN = length(jc) * length(jr); %#ok<NASGU>

              % index at vertex. V(i)
              i = ir + (ic - 1) * nRow;
              j = repmat(jr, 1, length(jc)) + repmat((jc -1) * nRow, length(jr), 1);
              j = reshape(j, length(jc) * length(jr), 1); % a col vector

              % spatial location distance (disimilarity)
              XJ = X(j, 1, :);
              XI = repmat(X(i, 1, :), length(j), 1);
              DX = XI - XJ;
              DX = sum(abs(DX), 3); % squared euclid distance

              % |X(i) - X(j)| <= r (already satisfied if block distance measurement)
              constraint = find(sqrt(DX) <= r);
              j = j(constraint);
              DX = DX(constraint);

              % feature vector disimilarity
              FJ = F(j, 1, :);
              FI = repmat(F(i, 1, :), length(j), 1);
              DF = FI - FJ;
              DF = sum(abs(DF), 3); % squared euclid distance ( DF = sum(abs(DF), 3); % block distance)
              W = sparse(exp(-DF / (SI*SI)) .* exp(-DX / (SX*SX)));

          end
      end

      %%ncutPartition
      Seg = (1:N)';                             % Step 5. recursively repartition
      id = 'ROOT';                              % the first segment has whole nodes. [1 2 3 ... N]'
      % Compute D
      N = length(W);
      d = sum(W, 2);
      D = spdiags(d, 0, N, N); % diagonal matrix
      % Step 2 and 3. Solve generalized eigensystem (D -W)*S = S*D*U (12).
      warning off; %#ok<WNOFF> % let me stop warning
      [U,S] = eigs(D-W,D, 2, 'lm');  %#ok<NASGU>
      % 2nd smallest (1st smallest has all same value elements, and useless)
      U2 = U(:, 2);
      % Bipartition the graph at point that Ncut is minimized.
      t = mean(U2);
      t = fminsearch('NcutValue', t, [], U2, W, D);
      A = find(U2 > t);
      B = find(U2 <= t);
      % Step 4. Decide if the current partition should be divided
      x = (U2 > t);
      x = (2 * x) - 1;
      d = diag(D);
      k = sum(d(x > 0)) / sum(d);
      b = k / (1 - k);
      y = (1 + x) - b * (1 - x);
      ncut = (y' * (D - W) * y) / ( y' * D * y );
      %%itteration
      if (length(A) < sArea || length(B) < sArea) || ncut > sNcut
          Seg{1}   = (1:N)'; %#ok<NASGU>
          Id{1}   = id;   %#ok<NASGU> % for debugging
          Ncut{1} = ncut; %#ok<NASGU> % for duebugging
          return;
      end
      % Seg segments of A
      [SegA IdA NcutA] = NcutPartition(Seg(A), W(A, A), sNcut, sArea, [id '-A']);
      % Seg segments of B
      [SegB IdB NcutB] = NcutPartition(Seg(B), W(B, B), sNcut, sArea, [id '-B']);
      % concatenate cell arrays
      Seg  = [SegA SegB];
      Id   = [IdA IdB]; %#ok<NASGU>
      Ncut = [NcutA NcutB]; %#ok<NASGU>
      %%show
      Inc  = zeros(size(I),'uint8');
      for k=1:length(Seg)
       [r, c] = ind2sub(size(I),Seg{k});

       for i=1:length(r)
       Inc(r(i),c(i),1:3) = uint8(round(mean(V(Seg{k}, :))));
       end
      end
      Knc = length(Seg);

      end

      % needs:
      % NcutPartition
      % NcutValue

??? Error using ==> minus

Matrix dimensions must agree.

Error in ==> Nc at 57

[U,S] = eigs(D-W,D, 2, 'lm'); %#ok<NASGU>

Error in ==> demo4 at 86

segI = Nc(I, SI, SX, r, sNcut, sArea);

Answer 1

[Image Analyst]

Before line 57 in Nc, put these lines

whos D
whos W

Chances are they are not the same size and so they cannot be subtracted.

[Poonam]

yes

Name      Size            Bytes  Class     Attributes

D         4x4               104  double    sparse    

Name      Size            Bytes  Class     Attributes

W         4x1                80  double    sparse

what should i do know

[Image Analyst]

I don't know what all that code does, but you should. Why do you think you should subtract W from D when they are not the same size???? You did it so you must think there should be a reason to do it.