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function F = lbppyr(I, P)
% LBPPYR computes LBP features on scale-pyramid of input image.
%
% Synopsis:
% F = lbppyr(I, P)
%
% Description:
% Local Binary Pattern (LBP) is 1 Byte number which encodes grey-scale
% intensities of a given 3x3 window.
%
% For P = 1, LBPPYR computes LBP features for all 3x3 windows
% in the input image I. The LBP features are stucked to a column
% vector F.
%
% For P > 1, the input image I is down-scaled (P-1)-times to create
% a scale-pyramid of height P. Each subsequent level of the pyramid is
% obtained by downscaling the original image by 2. Having the pyramid,
% the LBP features are computed on each leavel of the pyramid and
% they are stucked to a column vector F.
%
% For more details on LBP see:
% Ojala, et. al: Multiresolution gray-scale and rotation invariant
% texture classification with local binary patterns. IEEE PAMI,
% 24(7):971-987,2002.
%
% Input:
% I [H x W (uint8)] Input image.
% lbp_pyramid [1 x 1] Height of the LBP pyramids.
%
% Output:
% F [nDim x 1] LBP features stucked to a column vector.
%
% Example:
% I = imread('./data/lena.jpg');
% F = lbppyr(I,4);
%
% Matlab code equivalent to LBPPYR_MEX.C:
%
% [h,w] = size(I);
% I = uint32(I);
% F = [];
% k = 1;
% while k <= P & min(w,h) >= 3
% k = k + 1;
% tmp = lbpfilter(double(I));
% tmp = tmp(2:end-1,2:end-1);
% F = [F; tmp(:)];
% if mod(w,2) == 1
% I = I(:,1:w-1);
% w= w - 1;
% end
% if mod(h,2) == 1
% I = I(1:h-1,:);
% h = h - 1;
% end
% I = I(1:2:h,1:2:w)+I(1:2:h,2:2:w)+I(2:2:h,1:2:w)+I(2:2:h,2:2:w);
% [h,w] = size(I);
% end
%
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