sampletest.m

这是利用matlab所写的ezw影像压缩法

% This is a test program that tests the EZW
% matrix X is an example matrix same as Shapiro's paper given

X=[63 -34 49 10 7 13 -12 7;
   -31 23 14 -13 3 4 6 -1;
   15 14 3 -12 5 -7 3 9;
   -9 -7 -14 8 4 -2 3 2;
   -5 9 -1 47 4 6 -2 2;
   3 0 -3 2 3 -2 0 4;
   2 -3 6 -4 3 6 3 6;
   5 11 5 6 0 3 -4 4];

X0=X;

Y0=max(X);
     Y1=max(Y0); 
     for i=0:12;
        if 2^i<Y1 & 2^i>0.5*Y1;
           threshold=2^i;   % get initial threshold T0;
           break;
        end;
     end;
     
     
     sublist=[];
     [xx,yy]=size(X);
     
     global N
     
     A=mapping(xx);
[m,n]=size(A);
k=1;  N=[]; 
 for k=1:m*n;
     flag=0;
     for i=1:m;
         if flag==1;
             break;
         end
         for j=1:n;
             if A(i,j)==k;
                 N=[N;i,j];
                 flag=1;
                 break;
             end
         end
     end
 end
                 
       order=1;  
while threshold ~= 0.5,  % if threshold~=1, do dominantpass and subordinatepass.
         
   threshold
   
   %Dominant Pass
   
   [D,X,sublist] = dominantpass(X,threshold,sublist); 
   
   DD{order}=D
     
    %Subordinate pass
    
    threshold=threshold/2;
    if threshold ==0.5,
        break;
    end
    
    
   S = subordinatepass(sublist,threshold);
   SS{order}=S
   order=order+1;
    
end

    
    
    
% EZW decoder 

 global N;
 [m,n]=size(N);% the size of initial image
               % m is the pixels of initial image
 XX=zeros(8); % initialize the reconstructured image to zero;
 initialthreshold=32;
 threshold=initialthreshold; % initial theshold ;
 
 sublist=[]; % sublist is the new position matrix 
             % for all significant coefficients 'p' and 'n';
             
             
for k=1:6; % laststeplevel=6; 
                
            RR=zeros(8); % reference matrix RR;
  
     [a,b]=size(DD{k}); % ?    
 
 % dominant pass
 
     i=1; j=1;
     while i<=m;
     
          if j>b; % b is the length of dominant pass vector
             break;
          end
    
          if RR(N(i,1),N(i,2))==1;
              i=i+1;
         
          else
             if DD{k}(j)=='p';
                XX(N(i,1),N(i,2))=threshold;
                RR(N(i,1),N(i,2))=1; %reference matrix =1;
                sublist=[sublist;N(i,1),N(i,2)];
             end
     
             if DD{k}(j)=='n';
                XX(N(i,1),N(i,2))=-threshold;
                RR(N(i,1),N(i,2))=1; %reference matrix =1;
                sublist=[sublist;N(i,1),N(i,2)];
                
             end
         
             if DD{k}(j)=='z';
                 
                RR(N(i,1),N(i,2))=1; %reference matrix =1;
               
             end
     
             if DD{k}(j)=='t';
                RR(N(i,1),N(i,2))=1; %reference matrix =1;
                RR=checkchildren(i,RR);% all zerotree's descendants are set to 1.
               
             end
             
             i=i+1;j=j+1;
      
          end
         
      end
 
 
 % subordinate pass
 
 %[xx,yy]=size(s{k});
 [xx,yy]=size(sublist);
 threshold=threshold/2;
 
   for i=1:xx;
       
       if k==6 |threshold==0.5;
           break;
       end
       
      if SS{k}(i)==1;
         if XX(sublist(i,1),sublist(i,2))>0;
           
            XX(sublist(i,1),sublist(i,2))= XX(sublist(i,1),sublist(i,2))+ threshold;
            
         else 
             
            XX(sublist(i,1),sublist(i,2))= XX(sublist(i,1),sublist(i,2))-threshold;
           
         end

      end
   end
   
  threshold
  k
  XX
end

initialiamge=X0
reconstructuredimage=XX
difference=XX-X0