function ie=sep_ibm(x,i)

% SEP_IBM STFT-domain source separation via ideal binary masking
%
% ie=sep_ibm(x,i)
%
% Inputs:
% x: nchan x nsampl matrix containing nchan time-domain mixture signals
% with nsampl samples
% i: nsrc x nsampl x nchan matrix containing the the true spatial source
% images of nsrc sources
%
% Output:
% ie: nsrc x nsampl x nchan matrix containing the estimated spatial source
% images
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Copyright 2008 Emmanuel Vincent
% This software is distributed under the terms of the GNU Public License
% version 3 (http://www.gnu.org/licenses/gpl.txt)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


%%% Errors and warnings %%%
if nargin<2, error('Not enough input arguments.'); end
[nchan,nsampl]=size(x);
[nsrc,nsampl2,nchan2]=size(i);
if nsampl2~=nsampl, error('The number of samples is different within the mixture and the true source images.'); end
if nchan2~=nchan, error('The number of channels is different within the mixture and the true source images.'); end

%%% STFT %%%
X=stft_multi(x);
[nbin,nfram,nchan]=size(X);
I=reshape(stft_multi(reshape(permute(i,[1 3 2]),nsrc*nchan,nsampl)),nbin,nfram,nsrc,nchan);

%%% Computing ideal binary masks %%%
W=zeros(nbin,nfram,nsrc);
disto=zeros(nbin,nfram,nsrc);
for j=1:nsrc,
    disto(:,:,j)=sum(abs(permute(I(:,:,j,:),[1 2 4 3])-X).^2,3)+sum(sum(abs(I(:,:,[1:j-1 j+1:nsrc],:)).^2,4),3);
end
[disto,ind]=min(disto,[],3);
W((1:nbin).'*ones(1,nfram)+ones(nbin,1)*nbin*(0:nfram-1)+(ind-1)*nbin*nfram)=1;

%%% Applying the masks %%%
Ie=repmat(W,[1 1 1 nchan]).*repmat(permute(X,[1 2 4 3]),[1 1 nsrc 1]);

%%% ISTFT %%%
ie=istft_multi(Ie,nsampl);

return;