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