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1 function y = sampgrid(x,blocksize,varargin)
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2 %SAMPGRID Sample a multi-dimensional matrix on a regular grid.
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3 % Y = SAMPGRID(X,BLOCKSIZE,I1,I2,...,Ip) extracts block samples of size
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4 % BLOCKSIZE from the p-dimensional matrix X, arranging the samples as the
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5 % column vectors of the matrix Y. The locations of the (1,1,..,1)-th
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6 % elements of each block are given in the index vectors I1,I2,..Ip. The
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7 % total number of samples taken is length(I1)xlength(I2)x...xlength(Ip).
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8 % BLOCKSIZE should either be a p-element vector of the form [N1,N2,...Np],
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9 % or a scalar N which is shorthand for the square block size [N N ... N].
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10 %
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11 % Example: Sample a set of blocks uniformly from a 2D image.
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12 %
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13 % n = 512; blocknum = 20000; blocksize = [8 8];
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14 % im = rand(n,n);
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15 % [i1,i2] = reggrid(size(im)-blocksize+1, blocknum);
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16 % blocks = sampgrid(im, blocksize, i1, i2);
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17 %
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18 % See also REGGRID.
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19
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20 % Ron Rubinstein
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21 % Computer Science Department
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22 % Technion, Haifa 32000 Israel
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23 % ronrubin@cs
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24 %
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25 % November 2007
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26
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27
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28 p = ndims(x);
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29 if (p==2 && any(size(x)==1) && length(blocksize)==1)
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30 p = 1;
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31 end
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32
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33 if (numel(blocksize)==1)
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34 blocksize = ones(1,p)*blocksize;
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35 end
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36
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37 n = zeros(1,p);
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38 for i = 1:p
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39 n(i) = length(varargin{i});
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40 end
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41
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42 nsamps = prod(n);
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43
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44 % create y of the same class as x
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45 y = zeros(prod(blocksize),nsamps,class(x));
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46
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47 % ids() contains the index of the current block in I1..Ip
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48 ids = ones(p,1);
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49
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50 % block_ids contains the indices of the current block in X
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51 block_ids = cell(p,1);
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52 for j = 1:p
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53 block_ids{j} = varargin{j}(1) : varargin{j}(1)+blocksize(j)-1;
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54 end
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55
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56 for k = 1:nsamps
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57 block = x(block_ids{:});
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58 y(:,k) = block(:);
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59
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60 % increment ids() and block_ids{}
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61 if (k<nsamps)
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62 j = 1;
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63 while (ids(j) == n(j))
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64 ids(j) = 1;
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65 block_ids{j} = varargin{j}(1) : varargin{j}(1)+blocksize(j)-1;
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66 j = j+1;
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67 end
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68 ids(j) = ids(j)+1;
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69 block_ids{j} = varargin{j}(ids(j)) : varargin{j}(ids(j))+blocksize(j)-1;
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70 end
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71 end
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72
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