## Copyright (C) 2008 SÃ¸ren Hauberg ## ## This program is free software; you can redistribute it and/or modify ## it under the terms of the GNU General Public License as published by ## the Free Software Foundation; either version 3 of the License, or ## (at your option) any later version. ## ## This program is distributed in the hope that it will be useful, ## but WITHOUT ANY WARRANTY; without even the implied warranty of ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ## GNU General Public License for more details. ## ## You should have received a copy of the GNU General Public License ## along with this program; if not, write to the Free Software ## Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA ## -*- texinfo -*- ## @deftypefn {Function File} {@var{E} =} entropyfilt (@var{im}) ## @deftypefnx{Function File} {@var{E} =} entropyfilt (@var{im}, @var{domain}) ## @deftypefnx{Function File} {@var{E} =} entropyfilt (@var{im}, @var{domain}, @var{padding}, ...) ## Computes the local entropy in a neighbourhood around each pixel in an image. ## ## The entropy of the elements of the neighbourhood is computed as ## ## @example ## @var{E} = -sum (@var{P} .* log2 (@var{P}) ## @end example ## ## where @var{P} is the distribution of the elements of @var{im}. The distribution ## is approximated using a histogram with @var{nbins} cells. If @var{im} is ## @code{logical} then two cells are used. For other classes 256 cells ## are used. ## ## When the entropy is computed, zero-valued cells of the histogram are ignored. ## ## The neighbourhood is defined by the @var{domain} binary mask. Elements of the ## mask with a non-zero value are considered part of the neighbourhood. By default ## a 9 by 9 matrix containing only non-zero values is used. ## ## At the border of the image, extrapolation is used. By default symmetric ## extrapolation is used, but any method supported by the @code{padarray} function ## can be used. Since extrapolation is used, one can expect a lower entropy near ## the image border. ## ## @seealso{entropy, paddarray, stdfilt} ## @end deftypefn function retval = entropyfilt (I, domain = true (9), padding = "symmetric", varargin) ## Check input if (nargin == 0) error ("entropyfilt: not enough input arguments"); endif if (!ismatrix (I)) error ("entropyfilt: first input must be a matrix"); endif if (!ismatrix (domain)) error ("entropyfilt: second input argument must be a logical matrix"); endif domain = (domain > 0); ## Get number of histogram bins if (islogical (I)) nbins = 2; else nbins = 256; endif ## Convert to 8 or 16 bit integers if needed switch (class (I)) case {"double", "single", "int16", "int32", "int64", "uint16", "uint32", "uint64"} min_val = double (min (I (:))); max_val = double (max (I (:))); if (min_val == max_val) retval = zeros (size (I)); return; endif I = (double (I) - min_val)./(max_val - min_val); I = uint8 (255 * I); case {"logical", "int8", "uint8"} ## Do nothing otherwise error ("entropyfilt: cannot handle images of class '%s'", class (I)); endswitch size (I) ## Pad image pad = floor (size (domain)/2); I = padarray (I, pad, padding, varargin {:}); even = (round (size (domain)/2) == size (domain)/2); idx = cell (1, ndims (I)); for k = 1:ndims (I) idx {k} = (even (k)+1):size (I, k); endfor I = I (idx {:}); size (I) ## Perform filtering retval = __spatial_filtering__ (I, domain, "entropy", I, nbins); endfunction

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