matlab2维小波变换经典程序-2维小波变换经典程序 .txt

 
%  FWT_DB.M;
%  此示意程序用DWT实现二维小波变换
%  编程时间2004-4-10，编程人沙威
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clear;clc;
T=256;       %  图像维数
SUB_T=T/2;   %  子图维数
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%  1.调原始图像矩阵
load wbarb;  %  下载图像
f=X;         %  原始图像
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%  2.进行二维小波分解
l=wfilters('db10','l');    %  db10（消失矩为10)低通分解滤波器冲击响应（长度为20）
L=T-length(l);
l_zeros=[l,zeros(1,L)];    %  矩阵行数与输入图像一致，为2的整数幂
h=wfilters('db10','h');    %  db10（消失矩为10)高通分解滤波器冲击响应（长度为20）
h_zeros=[h,zeros(1,L)];    %  矩阵行数与输入图像一致，为2的整数幂
for i=1:T;   %  列变换
    row(1:SUB_T,i)=dyaddown( ifft( fft(l_zeros).*fft(f(:,i)') ) ).';    %  圆周卷积<->FFT
    row(SUB_T+1:T,i)=dyaddown( ifft( fft(h_zeros).*fft(f(:,i)') ) ).';  %  圆周卷积<->FFT
end;
for j=1:T;   %  行变换
    line(j,1:SUB_T)=dyaddown( ifft( fft(l_zeros).*fft(row(j,:)) ) );    %  圆周卷积<->FFT
    line(j,SUB_T+1:T)=dyaddown( ifft( fft(h_zeros).*fft(row(j,:)) ) );  %  圆周卷积<->FFT

end;
decompose_pic=line;  %  分解矩阵
%  图像分为四块
lt_pic=decompose_pic(1:SUB_T,1:SUB_T);      %  在矩阵左上方为低频分量--fi(x)*fi(y)
rt_pic=decompose_pic(1:SUB_T,SUB_T+1:T);    %  矩阵右上为--fi(x)*psi(y)
lb_pic=decompose_pic(SUB_T+1:T,1:SUB_T);    %  矩阵左下为--psi(x)*fi(y)
rb_pic=decompose_pic(SUB_T+1:T,SUB_T+1:T);  %  右下方为高频分量--psi(x)*psi(y)
 
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%  3.分解结果显示
figure(1);
colormap(map);
subplot(2,1,1);
image(f);  %  原始图像  
title('original pic');
subplot(2,1,2);
image(abs(decompose_pic));  %  分解后图像
title('decomposed pic');
figure(2);
colormap(map);
subplot(2,2,1);
image(abs(lt_pic));  %  左上方为低频分量--fi(x)*fi(y)
title('\Phi(x)*\Phi(y)');
subplot(2,2,2);
image(abs(rt_pic));  %  矩阵右上为--fi(x)*psi(y)
title('\Phi(x)*\Psi(y)');
subplot(2,2,3);
image(abs(lb_pic));  %  矩阵左下为--psi(x)*fi(y)
title('\Psi(x)*\Phi(y)');