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PCANet_FeaExt.m
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PCANet_FeaExt.m
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function [featureImages_stage1,featureImages_stage2] = PCANet_FeaExt(InImg,V,PCANet)
% =======INPUT=============
% InImg Input images (cell)
% V given PCA filter banks (cell)
% PCANet PCANet parameters (struct)
% .PCANet.NumStages
% the number of stages in PCANet; e.g., 2
% .PatchSize
% the patch size (filter size) for square patches; e.g., [5 3]
% means patch size equalt to 5 and 3 in the first stage and second stage, respectively
% .NumFilters
% the number of filters in each stage; e.g., [16 8] means 16 and
% 8 filters in the first stage and second stage, respectively
% .HistBlockSize
% the size of each block for local histogram; e.g., [10 10]
% .BlkOverLapRatio
% overlapped block region ratio; e.g., 0 means no overlapped
% between blocks, and 0.3 means 30% of blocksize is overlapped
% .Pyramid
% spatial pyramid matching; e.g., [1 2 4], and [] if no Pyramid
% is applied
% =======OUTPUT============
% f PCANet features (each column corresponds to feature of each image)
% BlkIdx index of local block from which the histogram is compuated
% =========================
addpath('./Utils')
if length(PCANet.NumFilters)~= PCANet.NumStages;
display('Length(PCANet.NumFilters)~=PCANet.NumStages')
return
end
NumImg = length(InImg);
OutImg = InImg;
ImgIdx = (1:NumImg)';
clear InImg;
for stage = 1:PCANet.NumStages
[OutImg ImgIdx] = PCA_output(OutImg, ImgIdx, ...
PCANet.PatchSize(stage), PCANet.NumFilters(stage), V{stage});
if stage == 1
featureImages_stage1 = OutImg;
else
featureImages_stage2 = OutImg;
end
end
%