debaselinepower.txt

基于matlab的图像处理中滤波的一些M文件源码。rar文件。

function myfilter(); 
clear all; 
% readfile = 'F:\project\experimentdata\basedrift\data0427lead9.dat';  
% readfile = 'F:\project\experimentdata\basedrift\data7.dat';  
readfile = 'F:\project\experimentdata\basedrift\data18.dat';  
 
 
 fid = fopen(readfile,'r');      %把filename文件名的内容读出，放f中。 
 [f,count] = fread(fid,'short'); 
 fclose(fid);                    %关闭该文件; 
 datalength = 3000; 
 s = f(1000:4000); 
maxlev=7;                        %分解6尺度 
[C,L] = wavedec(s,maxlev,'coif3'); 
 
figure(1); 
%绘出分解后重构的的逼近信息和细节细节 
AA1=wrcoef('a',C,L,'coif3',1); 
AA2=wrcoef('a',C,L,'coif3',2); 
AA3=wrcoef('a',C,L,'coif3',3); 
AA4=wrcoef('a',C,L,'coif3',4); 
AA5=wrcoef('a',C,L,'coif3',5); 
AA6=wrcoef('a',C,L,'coif3',6); 
AA7=wrcoef('a',C,L,'coif3',7); 
 
 DD1=wrcoef('d',C,L,'coif3',1); 
 DD2=wrcoef('d',C,L,'coif3',2); 
 DD3=wrcoef('d',C,L,'coif3',3); 
 DD4=wrcoef('d',C,L,'coif3',4); 
 DD5=wrcoef('d',C,L,'coif3',5); 
 DD6=wrcoef('d',C,L,'coif3',6); 
 DD7=wrcoef('d',C,L,'coif3',7); 
 
%提取分解后逼近系数和细节系数 
A1=appcoef(C,L,'coif3',1); 
A2=appcoef(C,L,'coif3',2); 
A3=appcoef(C,L,'coif3',3); 
A4=appcoef(C,L,'coif3',4); 
A5=appcoef(C,L,'coif3',5); 
A6=appcoef(C,L,'coif3',6); 
A7=appcoef(C,L,'coif3',7); 
 
D1=detcoef(C,L,1); 
D2=detcoef(C,L,2); 
D3=detcoef(C,L,3); 
D4=detcoef(C,L,4); 
D5=detcoef(C,L,5); 
D6=detcoef(C,L,6); 
D7=detcoef(C,L,7); 
  
yUp = 2000; 
yDn = -2000; 
% yUp = 500; 
% yDn = -500; 
 
subplot(8,2,1); 
plot(s); 
title('original'); 
axis([0,datalength,-500,500]); 
subplot(8,2,3); 
plot(AA1); 
ylabel('A1'); 
axis([0,datalength,-500,500]); 
subplot(8,2,5); 
plot(AA2); 
ylabel('A2'); 
axis([0,datalength,-500,500]); 
subplot(8,2,7); 
plot(AA3); 
ylabel('A3'); 
axis([0,datalength,-500,500]); 
subplot(8,2,9); 
plot(AA4); 
ylabel('A4'); 
axis([0,datalength,-500,500]); 
subplot(8,2,11); 
plot(AA5); 
ylabel('A5'); 
axis([0,datalength,-500,500]); 
subplot(8,2,13); 
plot(AA6); 
ylabel('A6'); 
axis([0,datalength,-500,500]); 
subplot(8,2,15); 
plot(AA7); 
ylabel('A7'); 
axis([0,datalength,-500,500]); 
 
 subplot(8,2,4); 
 plot(DD1); 
ylabel('D1'); 
 axis([0,datalength,-20,20]); 
 subplot(8,2,6); 
 plot(DD2); 
ylabel('D2'); 
axis([0,datalength,-50,50]); 
 subplot(8,2,8); 
 plot(DD3); 
ylabel('D3'); 
axis([0,datalength,-200,200]); 
 subplot(8,2,10); 
 plot(DD4); 
ylabel('D4'); 
axis([0,datalength,-200,200]); 
 subplot(8,2,12); 
 plot(DD5); 
ylabel('D5'); 
axis([0,datalength,-200,200]); 
 subplot(8,2,14); 
 plot(DD6); 
ylabel('D6'); 
axis([0,datalength,-200,200]); 
 subplot(8,2,16); 
 plot(DD7); 
ylabel('D7'); 
axis([0,datalength,-200,200]); 
 figure(2); 
 %将第一尺度置零 
%  D1= zeros(1,length(D1)); 
%  D2= zeros(1,length(D2)); 
 A7=zeros(1,length(A7)); 
 C2 = [A7,D7',D6',D5',D4',D3',D2',D1'];  % 
 s2 = waverec(C2,L,'coif3'); 
  
 subplot(311); 
 plot(s); 
 axis([0,datalength,yDn,yUp]); 
  
 %滤工频 
b = [1,1,1,1,1,1,1,1,1,1]; 
a = [10]; 
nFactor = 1.5   %工频需要适当放大滤波后的数据 
% b = [0.95,0,0,0,0,0,0,0,0,0,-0.95]; 
% a = [1,0,0,0,0,0,0,0,0,0,-0.9]; 
% nFactor = 1;   %工频需要适当放大滤波后的数据 
 
yy = filter(b,a,s2); 
%修改幅值 
for i=1:datalength 
    yy(i) = yy(i)*nFactor; 
end 
 subplot(312); 
 plot(yy); 
 axis([0,datalength,yDn,yUp]); 
  
%噪声信号 
for i = 1:datalength; 
    noisesig(i) = s(i) - yy(i); 
end 
subplot(313); 
 plot(noisesig); 
 axis([0,datalength,yDn,yUp]);