matlab小波变换函数的总结与程序

1、小波去噪举例MATLAB中用wnoise函数测试去噪算法sqrt_snr=3;init=231434;x,xn=wnoise(3,11,sqrt_snr,init; % 加噪,信噪比为3subplot(3,2,1,plot(xtitle('original test function'subplot(3,2,2,plot(xntitle('noised function'lev=5;xd=wden(x,'heursure','s','one',lev,'sym8'%利用小波对一维信号进行降噪, XD

2、为降噪后的%信号,CXD,LXD为XD的小波分解结构% 's' or 'h'决定阈值的使用方式,SCAL决定阈值是%否随噪声变化:'one' 不调整,'sln'对第一层系%数的层噪声分别进行估计和调整;'mln'对各层%系数的层噪声分别进行估计和调整; subplot(3,2,3,plot(xdtitle('One de-noised function'xd=wden(x,'heursure','s','sln',lev,'sym8's

3、ubplot(3,2,4,plot(xdtitle('Sln de-noised function'xd=wden(x,'sqtwolog','s','sln',lev,'sym8'% 固定阈值选择算法去噪subplot(3,2,5,plot(xdtitle('Sqtwolog de-noised function'c,l=wavedec(x,lev,'sym8'subplot(3,2,6,plot(xdtitle('CL de-noised function' MA

4、TLAB中图像噪声处理举例load sinsin;colormap('default'subplot(1,3,1,image(X;title('original image'axis('square'init=231434;randn('seed',init;X=X+18*randn(size(X; %产生噪声信号subplot(1,3,2,image(x;title('noised image'axis('square'thr,sorh,keepapp=ddencmp('den',

5、'wv',x;%自动生成小波去躁或压缩的阈值选择方案,也%就是寻找默认值xc,cxc,lxc,perf0,perfl2=wdencmp('gbl',x,'sym4',2,thr,sorh,keepapp;%使用全局阈值进行%图象降噪subplot(1,3,3,image(xc;title('denoised image'axis('square' 可见,含躁图像的噪声含量很强,利用小波去躁,可以有效去除躁声,同时保留了边界。Wdencmp函数xc,cxc,lxc,perf0,perfl2=wdencmp('gbl',x,'sym4',2,thr,sorh,keepapp 是使用小波进行一维或二维小波压缩或降噪的函数。前面的语句是对于输入的一维或二维信号X,使用全局正阈值THR,由小波系数阈值得到降噪或压缩后的信号XC。附加的输出变量cxc,lxc是XC的小波分解结构;perf0,pe