维小波变换MATLAB实现

1、二维小波变换matlab实现 dwt2函数 功能：二维离散小波变换 格式：ca,ch,cv,cd=dwt2(x,wname) ca,ch,cv,cd=dwt2(x,lo_d,hi_d) 说明：ca,ch,cv,cd=dwt2(x,wname)使用指定的小波基函数wname对二维信号x进行二维离散小波变幻；ca，ch,cv,cd分别为近似分量、水平细节分量、垂直细节分量和对角细节分量；ca,ch,cv,cd=dwt2(x,lo_d,hi_d)使用指定的分解低通和高通滤波器lo_d和hi_d分解信号x。 load woman; nbcol = size(map,1);%返回矩阵的行数和列数 ca1

2、,ch1,cv1,cd1 = dwt2(x,db1); cod_x=wcodemat(x,nbcol);%返回矩阵x的编码矩阵，nbcol为编码的最大值 cod_ca1=wcodemat(ca1,nbcol); cod_ch1=wcodemat(ch1,nbcol); cod_cv1=wcodemat(cv1,nbcol); cod_cd1=wcodemat(cd1,nbcol); dec2d=cod_ca1,cod_ch1;cod_cv1,cod_cd1; subplot(1,2,1),imshow(cod_x,); title(量化后的图像); subplot(1,2,2),imshow(

3、dec2d,); title(二维离散小波分解后的图像); idwt2函数 功能：二维离散小波反变换 格式：x=idwt2(ca,ch,cv,cd,wname) x=idwt2(ca,ch,cv,cd,lo_r,hi_r) x=idwt2(ca,ch,cv,cd,wname,s) x=idwt2(ca,ch,cv,cd,lo_r,hi_r,s) 说明：x=idwt2(ca,ch,cv,cd,wname)由信号小波分解的近似信号ca和细节信号ch、ch、cv、cd经小波反变换重构原信号x；x=idwt2(ca,ch,cv,cd,lo_r,hi_r)使用指定的重构低通和高通滤波器lo_r和hi_r

4、重构原信号x；x=idwt2(ca,ch,cv,cd,wname,s)和x=idwt2(ca,ch,cv,cd,lo_r,hi_r,s)返回中心附近的s个数据点。 load woman; sx=size(x); ca1,ch1,cv1,cd1=dwt2(x,db4); a0=idwt2(ca1,ch1,cv1,cd1,db4,sx); subplot(1,2,1),imshow(x,) title(原始图像); subplot(1,2,2),imshow(a0,) title(由二维小波分解重构后的图像); wavedec2函数 功能：二维信号的多层小波分解 格式：c,s=wavedec2(x

5、,n,wname) c,s=wavedec2(x,n,lo_d,hi_d) 说明：c,s=wavedec2(x,n,wname)用小波基函数wname对二维信号x进行n层分解；c,s=wavedec2(x,n,lo_d,hi_d)用指定的分解低通和高通滤波器lo_d和hi_d分解信号x。 waverec2函数 说明：二维信号的多层小波重构 格式：x=waverec2(c,s,wname) x=waverec2(c,s,lo_r,hi_r) 说明：x=waverec2(c,s,wname)由多层二维小波分解的结果c、s重构原始信号x，wname为使用的小波基函数；x=waverec2(c,s,l

6、o_r,hi_r)使用重构低通和高通滤波器lo_r和hi_r重构原信号。 load woman; c,s=wavedec2(x,2,sym4); a0=waverec2(c,s,sym4); subplot(1,2,1),imshow(x,) title(原始图像); subplot(1,2,2),imshow(a0,) title(重构后的图像);appcoef2提取二维信号小波分解的近似分量 load woman; c,s=wavedec2(x,3,db1);%用db1小波进行三层分解 ca1=appcoef2(c,s,db1,1);%提取一层近似分量 ca2=appcoef2(c,s,d

7、b2,2);%提取二层近似分量 imshow(x,); title(原始图像); figure,imshow(ca1,) title (第一层近似分量); figure,imshow(ca2,) title(第二层近似分量);detcoef2提取二维信号小波分解的细节分量load woman;c,s=wavedec2(x,3,db1);chd2=detcoef2(h,c,s,1);cvd2=detcoef2(v,c,s,1);cdd2=detcoef2(d,c,s,1);imshow(x,)title(原始图像);figuresubplot(1,3,1),imshow(chd2,)title(

8、第一层分解的水平细节);subplot(1,3,2),imshow(cvd2,)title(第一层分解的垂直细节);subplot(1,3,3),imshow(cdd2,)title(第一层分解的对角细节);wrcoef2由多层小波分解重构某一层的分解信号 clear allload wbarb;image(x);colormap(map);colorbar;i=ind2gray(x,map);figure;i=imadjust(i,stretchlim(i),0,1);imshow(i);%j=imadjust(i,low_in;high_in,low_out,high_out) 将 i 中

9、的亮度值映射到 j 中的新值wname=sym2;c,s=wavedec2(i,2,wname);ca1=appcoef2(c,s,wname,1);ch1,cv1,cd1=detcoef2(all,c,s,1);ca2=appcoef2(c,s,wname,2);ch2,cv2,cd2=detcoef2(all,c,s,2);a1=wrcoef2(a,c,s,wname,1);h1=wrcoef2(h,c,s,wname,1);v1=wrcoef2(v,c,s,wname,1);d1=wrcoef2(d,c,s,wname,1);a2=wrcoef2(a,c,s,wname,2);h2=wr

10、coef2(h,c,s,wname,2);v2=wrcoef2(v,c,s,wname,2);d2=wrcoef2(d,c,s,wname,2);figure;subplot(2,2,1);a1=abs(a1);a1=imadjust(a1,stretchlim(a1),0,1);imshow(a1);title(approximation a1)subplot(2,2,2);h1=abs(h1);h1=imadjust(h1,stretchlim(h1),0,1);imshow(h1);title(horizontal detail h1)subplot(2,2,3);v1=abs(v1);

11、v1=imadjust(v1,stretchlim(v1),0,1);imshow(v1);title(vertical detail v1)subplot(2,2,4);d1=abs(d1);d1=imadjust(d1,stretchlim(d1),0,1);imshow(d1);title(diagonal detail d1)figure;subplot(2,2,1);a2=abs(a2);a2=imadjust(a2,stretchlim(a2),0,1);imshow(a2);title(approximation a2)subplot(2,2,2);h2=abs(h2);h2=i

12、madjust(h2,stretchlim(h2),0,1);imshow(h2);title(horizontal detail h2)subplot(2,2,3);v2=abs(v2);v2=imadjust(v2,stretchlim(v2),0,1);imshow(v2);title(vertical detail v2)subplot(2,2,4);d2=abs(d2);d2=imadjust(d2,stretchlim(d2),0,1);imshow(d2);title(diagonal detail d2)upcoef2由多层小波分解重构近似分量或细节分量 load woman;c,s=wavedec2(x,2,db4);siz=s(size(s,1),:);cal=appcoef2(c,s,db4,1);a1=upcoef2(a,cal,db4,1,siz);chd1=detcoef2(h,c,s,1);hd1=upcoef2(h,chd1,db4,1,siz);cvd1=detcoef2(v,c,s,1);vd1=upcoef2(h,cvd1,db4,1,siz);cdd1=detcoef2(d,c,s,1