%IM_PROFILE Fixed mapping computating horizontal and vertical image profiles
%
% P = IM_PROFILE(A,NX,NY)
% P = A*IM_PROFILE([],NX,NY)
% P = A*IM_PROFILE(NX,NY)
%
% INPUT
% A Dataset with object images dataset (possibly multi-band)
% NX Number of bins for horizontal profile
% NY Number of bins for vertical profile
%
% OUTPUT
% P Dataset with profiles replacing images (possibly multi-band)
%
% DESCRIPTION
% Computes for the images in A a 1*(NX+NY) vector P storing the horizontal and
% vertical profile (i.e. normalized image projections) given by NX respectively
% NY points. Because of the normalization holds sum(P) = 1.
% The computation is based on a bilinear interpolation of A to an image of NX*NY
% points. Consequently is the horizontal profile (P(1:NX)) slightly dependent
% on NY and the vertical profile (P(NX+1:NX+NY)) slightly dependent on NX.
% Defaults : NY = NX, NX = 16.
%
% SEE ALSO (<a href="http://37steps.com/prtools">PRTools Guide</a>)
% DATASETS, DATAFILES
% Copyright: R.P.W. Duin, r.p.w.duin@37steps.com
% Faculty EWI, Delft University of Technology
% P.O. Box 5031, 2600 GA Delft, The Netherlands
function b = im_profile(varargin)
argin = shiftargin(varargin,'scalar');
argin = setdefaults(argin,[],16,[]);
if mapping_task(argin,'definition')
b = define_mapping(argin,'fixed');
b = setname(b,'Image patches');
else
[a,nx,ny] = deal(argin{:});
if isa(a,'prdataset') % allows datafiles too
isobjim(a);
b = filtim(a,mfilename,{nx,ny});
elseif isa(a,'double') | isa(a,'dip_image') % here we have a single image
if isa(a,'dip_image'), a = double(a); end
if isempty(ny)
ny = nx;
end
if any([nx,ny] < 4)
b = imresize(a,10*[ny,nx],'bilinear');
sx = sum(reshape(sum(b,1),10,nx),1);
sy = sum(reshape(sum(b,2)',10,ny),1);
s = sum(sx);
b = [sx sy]/s;
else
b = imresize(a,[ny,nx],'bilinear');
s = sum(b(:));
b = [sum(b,1) sum(b,2)']/s;
end
end
end
return