%IM_HIST Histogramming of image dataset (datafile)
%
% H = IM_HIST(A,N)
% H = A*IM_HIST([],N)
% H = A*IM_HIST(N)
% H = IM_HIST(A,X)
% H = A*IM_HIST([],X)
% H = A*IM_HIST(X)
%
% INPUT
% A Dataset or datafile
% N Number of bins, default 256
% X User defined histogram bins (centers)
%
% OUTPUT
% H Dataset or datafile with histogram bin frequencies
%
% DESCRIPTION
% For every object in the dataset A the set of feature values (for images
% pixels)is mapped into a histogram, specifying for each bin the number of
% features having a value as specified for that bin. If H is converted to a
% dataset it has a feature size equal to the number of bins times the
% number of bands in the image. So color images return a histogram for
% every band.
%
% Use HISTM if the bin positions have to be determined automatically is a
% 'training' stage from some images.
%
% SEE ALSO (<a href="http://37steps.com/prtools">PRTools Guide</a>)
% DATASETS, DATAFILES, MAPPINGS, HIST, HISTM
function h = im_hist(varargin)
argin = shiftargin(varargin,'double');
[a,bins] = setdefaults(argin,[],256);
if mapping_task(argin,'definition')
h = define_mapping(argin,'fixed','histogram');
elseif isdatafile(a)
h = addpostproc(a,im_hist(bins));
elseif isdataset(a)
if numel(bins) == 1
h = filtim(a,'imhist',bins);
else
m = size(a,1);
im = data2im(a(1,:));
nbands = size(im,3);
h = zeros(1,numel(bins),nbands,m);
t = sprintf('Histogramming %i objects: ',m);
prwaitbar(m,t);
for i=1:m
prwaitbar(m,i,[t num2str(i)]);
im = data2im(a(i,:));
for j=1:nbands
band = im(:,:,j);
h(1,:,j,i) = hist(band(:),bins);
end
end
prwaitbar(0);
h = setdata(a,im2obj(h,[1,numel(bins),nbands]));
end
else
error('Illegal input')
end