wadecdiping.m

这是偶自己的作品拉

function Wavelet_Vector_Comprssion()
%X=imread('j:\数字图像处理－活用Matlab程序\CH7\lena.bmp','bmp');
%[LL1,LH1,HL1,HH1]=dwtper2(X,'bior3.3');
%load lena
X=imread('E:\matlab1\LENA256.bmp','bmp');
%figure(100);imshow(uint8(X));title('original image');
%利用正交小波函数对X进行多尺度分解
%[C,S]=wavedec2(double(X),N,Wavelet_Name)是使用指定的小波基‘Wavelet_Name’对图像X进行N层分解
Wavelet_Name='db1';
%Wavelet_Scale=1;
[c,s]=wavedec2(double(X),2,Wavelet_Name);
%appcoef2用来提取二维信号小波分解的近似分量
%   提取一维小波系数
ca1=appcoef2(c,s,Wavelet_Name,1);

%detcoef2用来提取二维信号小波分解的细节分量
%D=detcoef2(O,C,S,N)，O指定细节分量的类型，
%当O=‘h’时，重构水平细节分量，当O=‘v’时，重构垂直细节分量，当O=‘d’时，重构细节细节分量
cv1=detcoef2('v',c,s,1);
ch1=detcoef2('h',c,s,1);
cd1=detcoef2('d',c,s,1);

%训练LL1频带码本，将码本大小设为128，维度为4 %
th=0.05;
nc=64;nd=4;
[cbLL1]=LBG(ca1,nc,nd,th); %LBG.m在L3.3节中




%利用一层小波变换加上向量量化进行Lena图像压缩%
%输入一幅Lena图像%
X=imread('E:\matlab1\LENA256.bmp','bmp');
%load lena
[M,N]=size(X);
%使用Matlab中Wavelet工具箱的周期性小波变换函数dwtper2.m%
%并使用双正交小波bior3.3进行一层小波变换%
%[LL1,LH1,HL1,HH1]=dwtper2(X,'bior3.3');
[C,S]=wavedec2(double(X),2,Wavelet_Name);
%[C,S]=wavedec2(double(X),Wavelet_Scale,Wavelet_Name);
LL1=appcoef2(C,S,Wavelet_Name,1);
LH1=detcoef2('v',C,S,1);
HL1=detcoef2('h',C,S,1);
HH1=detcoef2('d',C,S,1);
%分别针对不同的频带进行向量量化，其中VQ.m置于L3.4节中%
[R_LL1,bitLL1]=VQ(LL1,cbLL1);
wt_Y(1:M/2,1:N/2)=R_LL1;


u=mean2(HL1);
sum1=0;
[m,n]=size(HL1)
for i=1:1:m
    for j=1:1:n
   if HL1(i,j)<u
        HL1(i,j)=0;
       sum1=sum1+1; 
   end
    end
end
sum1
u=mean2(LH1);
sum1=0;
[m,n]=size(LH1)
for i=1:1:m
    for j=1:1:n
   if LH1(i,j)<u
       LH1(i,j)=0;
       sum1=sum1+1; 
   end
    end
end
sum1
u=mean2(HH1);
sum1=0;
[m,n]=size(HH1)
for i=1:1:m
    for j=1:1:n
   if HH1(i,j)<u
        HH1(i,j)=0;
       sum1=sum1+1; 
   end
    end
end
sum1

%计算图像经过向量量化后的压缩率CR及失真PSNR%
totalbit=bitLL1          %花费的总位数  =4416
%Y=idwtper2(R_LL1,R_LH1,R_HL1,R_HH1,'bior3.3'); %反小波变换

%C2= [ HL1 LH2 HH2];
s2=s;
%a2=wrcoef2('a',R_LL2,s2,'db1',2);
%Y1=idwt2(R_LL2, HL2 ,LH2, HH2,'db1',size(LL1));
%figure(66);imshow(uint8(Y2));title('compressed image');

Y2=idwt2(R_LL1,HL1 ,LH1, HH1,'db1',size(X));
%size(a2)
figure(100);imshow(uint8(X));title('original image');
figure(200);imshow(uint8(Y2));title('compressed image');

%Y2=waverec2(C2,s2,'db1',1);
%size(a2)size(Y)=[128 128]
%figure(300);imshow(uint8(Y2));
X=double(X);
Y2=double(Y2);

MSE=(sum(sum((X-Y2).^2)))/(M*N)
PSNR=20*log10(255/sqrt(MSE))
CR=M*N*8/totalbit



%figure;imshow(uint8(Y));

%figure;imshow(uint8(c1));
%figure;imshow(uint8(c2));
%figure;imshow(uint8(ca2));