二维小波变换MATLAB实现课件

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。loadwoman;nbcol=size(map,1);%返回矩阵的行数和列数[cA1,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(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。loadwoman;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,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。loadwoman;[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loadwoman;[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,'db2',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loadwoman;[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('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');figure;subplot(2,2,1);a1=abs(a1);a1=imadjust(a1,stretchlim(a1),[0,1]);imshow(a1);title('approximationa1')subplot(2,2,2);h1=abs(h1);h1=imadjust(h1,stretchlim(h1),[0,1]);imshow(h1);title('horizontaldetailh1')subplot(2,2,3);v1=abs(v1);v1=imadjust(v1,stretchlim(v1),[0,1]);imshow(v1);title('verticaldetailv1')subplot(2,2,4);d1=abs(d1);d1=imadjust(d1,stretchlim(d1),[0,1]);imshow(d1);title('diagonaldetaild1')figure;subplot(2,2,1);a2=abs(a2);a2=imadjust(a2,stretchlim(a2),[0,1]);imshow(a2);title('approximationa2')subplot(2,2,2);h2=abs(h2);h2=imadjust(h2,stretchlim(h2),[0,1]);imshow(h2);title('horizontaldetailh2')subplot(2,2,3);v2=abs(v2);v2=imadjust(v2,stretchlim(v2),[0,1]);imshow(v2);title('verticaldetailv2')subplot(2,2,4);d2=abs(d2);d2=imadjust(d2,stretchlim(d2),[0,1]);imshow(d2);title('diagonaldetaild2')upcoef2由多层小波分解重构近似分量或细节分量loadwoman;[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);dd1=upcoef2('d',cdd1,'db4',1,siz);subplot(2,2,1),ims