function [Y,Xpad] = snn12(X,WINSZ,true)
% [Y,Xpad] = SNN(X[,WINSZ][,progress])
% perform symmetric nearest-neighbor nonlinear edge-preserving filtering on
% an intensity image
%
% * If no window size WINSZ is specified, the default is 5.
% * Setting progress to a nonzero value causes SSN to display
% the current row it is processing.
%
% Description:
% The SNN filter works by looking at each pair of pixels opposite the
% output (center) pixel. From each pair, the one that is closest to
% the output pixel is used to compute the output (mean of all selected
% pixels).
%
% Notes:
% Image is converted to double format for processing.
%
% Copyright Art Barnes, 2005 artbarnesieeeorg
if nargin >= 3
verboseFlag = true;
else
verboseFlag = false;
end
if nargin < 2
WINSZ = 3;
end
if ~isa(X,'double')
X = im2double(X);
end
PADDING = floor(WINSZ/2);
Xpad = padarray(X,[PADDING PADDING],'symmetric','pre');
[padRows,padCols] = size(Xpad);
Y = zeros(size(X));
nRowIters = length((PADDING+1):(padRows-PADDING));
count = 1;
for i = (PADDING+1):(padRows-PADDING)
for j = (PADDING+1):(padCols-PADDING)
% window
W = Xpad((i-PADDING):(i+PADDING),(j-PADDING):(j+PADDING));
Wtop = W(1:PADDING,:)';
Wtop = Wtop(:)';
Wtop = [Wtop W(PADDING+1,1:PADDING)];
Wbot = W((end-PADDING+1):end,:)';
Wbot = Wbot(:)';
Wbot = [W(PADDING+1,(end-PADDING+1):end) Wbot];
Wbot = fliplr(Wbot);
NN = [Wtop; Wbot];
NNdiff = abs(NN - W(PADDING+1,PADDING+1)); % or use X(i,j)
[y,ids] = min(NNdiff);
for k = 1:length(ids)
NNnearest(k) = NN(ids(k),k);
end
Y(i,j) = mean([NNnearest Xpad(i,j)]);
end
%if verboseFlag & ~mod(count,10)
% fprintf('SNN: %d/%d\n',count,nRowIters);
%end
count = count + 1;
end
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