%
% SingleHypoDisparity.m
%
% The single hypothesis scheme is where a single integer disparity 
% value is specified along with the index of the reference image
% that should be used for prediction.  The target image is predicted 
% by disparity compensating the specified reference image.
%

function [R, D, pdfout, predBlock] = ...
	SingleHypoDisparity(Itarget, Irefs, lambda, ...
						indices, pdfin, ...
						rowBlock, colBlock, ...
						blocksize)

R = 0;
D = 0;
J = inf;
i = 0;
r = (rowBlock-1)*blocksize + 1;
c = (colBlock-1)*blocksize + 1;
targetBlock = GetBlock(Itarget, r, c, blocksize);

for disparity = indices

  i = i+1;
  p_i = pdfin(i)/sum(pdfin);
  Rcurr = -log2(p_i) + 2;

  % left
  refBlock{1} = GetBlock(Irefs{1}, r, c+disparity, blocksize);
  % right
  refBlock{2} = GetBlock(Irefs{2}, r, c-disparity, blocksize);
  % top
  refBlock{3} = GetBlock(Irefs{3}, r+disparity, c, blocksize);
  % bottom
  refBlock{4} = GetBlock(Irefs{4}, r-disparity, c, blocksize);
  
  for j=1:4

	Dcurr = GetDistortion(refBlock{j}, targetBlock);
	Jcurr = Dcurr + lambda*Rcurr;
  
	if (Jcurr < J)
	  J = Jcurr;
	  R = Rcurr;
	  D = Dcurr;
	  predBlock = refBlock{j};
	  pdfout = zeros(size(pdfin));
	  pdfout(i) = 1;
	end
	
  end
  
  
end