xfemd2.m

在MATLAB环境下实现二维emd分解的实现

tic;
clear
clc
rs=imread('rs.jpg');
rs_tuceng=rs(:,:,1);     %%%%%%%%%%%%%%选择图图层%%%%%%%%%%%%%%%%%%%%%%%%
[m,n]=size(rs_tuceng);
for i=1:n
y=rs_tuceng(:,i);    
ip=double(y);       %%%%%%%%%待分解数据序列一维列向量%%%%%%%%%%%%%%
PRE_yuzhi=0.005; %%%%%%--偏差阈值%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
NUM1=20;         %%%%%%%--分解得到IMF分量的最多数目%%%%%%%%%%%%%%%%%%%%%%%%
NUM2=800;        %%%%%%%--提取IMF分量的最多筛分次数；%%%%%%%%%%%%%%%%
flag=0;
I=0;
num1=0;
num2=0;
N=length(ip);
x=1:N;
[max,max_No,min,min_No]=MaxMin(ip);
while(max_No(1)~=0 && min_No(1)~=0)
    if(num1>=NUM1) 
        break; 
    end
    while(1)
        num2=num2+1;
        [yy1,yy2]=Enovelope(x,max,max_No,min,min_No);
        mean=[(yy1+yy2)/2]';
        h1=ip-mean;
        [max,max_No,min,min_No]=MaxMin(h1);
        if(max_No(1)==0 || min_No(1)==0)
            flag=1;
            break;
        end
        [yy1,yy2]=Enovelope(x,max,max_No,min,min_No);
        mean=[(yy1+yy2)/2]';
        hmax=MaxMax(mean);
        N1=ZeroNum(h1);
        tiaojian1=hmax-PRE_yuzhi;
        tiaojian2=abs(length(max_No)+length(min_No)-N1);
        if((tiaojian1<0 && tiaojian2<=1) || num2<=NUM2)
            I=I+1;
            imf(:,I)=h1;
            break;
        else
            ip1=h1;
            [max,max_No,min,min_No]=MaxMin(ip1);
        end
    end
    
    if(flag==1)
        flag=0;
        break;
    else
        ip=ip-imf(:,I);
        num1=I;
        [max,max_No,min,min_No]=MaxMin(ip); 
    end
end
imf(:,I+1)=ip;
k=I+1;   %%%%%%%%%%%%%%%%%%分解的模式函数的个数%%%%%%%%%%%%%%%%%%
rs_imf1(:,i)=imf(:,1);
rs_imf2(:,i)=imf(:,2);
%rs_imf3(:,i)=imf(:,3);
%rs_imf4(:,i)=imf(:,4);
end
subplot(3,2,1)
image(rs)
colormap(gray)
subplot(3,2,2)
image(rs_tuceng)
colormap(gray)
subplot(3,2,3)
image(rs_imf1)
colormap(gray)
subplot(3,2,4)
image(rs_imf2)
colormap(gray)
%subplot(3,2,5)
%image(rs_imf3)
%colormap(gray)
%subplot(3,2,6)
%image(rs_imf4)
%colormap(gray)
toc