bilinear.m

各种SVM分类算法

function [Tmp]=bilinear(Img_in,W_set,H_set)
%  bilinear
%  Author: Zou Zhihuang
%  Data:   2008.1.22
% Input
%      Img -- Input Image
%      W   -- the width you want to set
%      H   -- the higth you want to set
% Output:
%      Tmp - Result Image 
[W_in,H_in,dim]=size(Img_in);
Tmp=uint8(zeros(W_set,H_set,dim));

w_scale=W_in/W_set;
h_scale=H_in/H_set;

for k=1:dim
 for i=1:W_set
    for j=1:H_set
        x=i*w_scale;
        y=j*h_scale;
        if(x==floor(x)) & (y==floor(y))  %旧坐标为整数时
            Tmp(i,j,k)=Img_in(int16(x),int16(y),k);
            %[x,floor(x),i,j]            
        else
%             if(floor(x)==0)|(floor(y)==0)
%              Tmp(i,j,k)=Img_in(1,1,k);
%              [i,j]
            if(floor(x)==0)|(floor(y)==0)     %added by zou
                Tmp(i,j,k)=Img_in(ceil(x),ceil(y),k);
                
            else
           x11=double(Img_in(floor(x),floor(y),k));
           x12=double(Img_in(floor(x),floor(y),k));
           x21=double(Img_in(floor(x),floor(y),k));
           x22=double(Img_in(floor(x),floor(y),k));                
      
          wx1=1-(x-floor(x));
          wx2=x-floor(x);
          wy1=1-(y-floor(y));
          wy2=y-floor(y);
          Tmp(i,j,k)=[wx1 wx2]*[x11 x12;x21 x22]*[wy1;wy2];  
           end   
        end
    end
 end
end