Wavelet-based image multiscale analysis of secret 2_matlab-wavelet analysis &matab implementation

1.MATLAB program Writing Step 1, the wavelet W (t) and the original function f (t) are compared to the beginning of the calculation coefficient c. The coefficient c indicates the similarity between the partial function and the wavelet.
2. Move the wavelet to the right K unit, get the wavelet w (t-k), repeat 1. Repeat the section to know that the function f ends.
3. Extend the wavelet W (t), get the wavelet W (T/2) and repeat the step 1,2.
4. Continuously expand the wavelet, repeat 1,2,3.
The Haar wavelets used here, the scaling function is [1 1], the wavelet function is [1-1], is the simplest small wave.
2.MATLAB Source Code and analysis

Clear All;close ALL;CLC;
Img=double (Imread (' ziheng.jpg '));
[M,n]=size (IMG);

[Ll,lh,hl,hh]=haar_dwt2d (IMG);  %dwt2 (IMG, ' Haar ') like
img=[ll LH; HL HH]; % one layer decomposition

imgn=zeros (m,n);
For I=0:M/2:M/2 for
    J=0:N/2:N/2
        [Ll,lh,hl,hh]=haar_dwt2d (I+1:I+M/2,J+1:J+N/2);% to decompose four images after one layer decomposition
        IMGN (I+1:I+M/2,J+1:J+N/2) =[ll LH; HL HH];  
    End
End
Imshow (IMGN)

function [Ll,lh,hl,hh]=haar_dwt2d (IMG)
    [M,n]=size (IMG);
    For i=1:m       % each row is decomposed
        [L,H]=HAAR_DWT (IMG (i,:));
        IMG (i,:) =[l H];
    End       -for j=1:n% each column is decomposed
       [L,h]=haar_dwt (IMG (:, j));
       IMG (:, j) =[l H];
    End
    % should not be added Mat2gray, but in order to have a good display effect on the addition of
    Ll=mat2gray (IMG (1:M/2,1:N/2));          % of the ranks are low-frequency  
    lh=mat2gray (img (1:m/2,n/2+1:n));        % line Low frequency column high-frequency
    hl=mat2gray (img (M/2+1:M,1:N/2));        % line High frequency column low-frequency
    hh=mat2gray (img (m/2+1:m,n/2+1:n));      % of the ranks are high-frequency end 

%HAAR_DWT.M
function [L,H]=HAAR_DWT (f)
    % does not do boundary processing, the picture preferably is 2^n*2^n type
    n=length (f);
    N=N/2;
    L=zeros (1,n);   % low-frequency Component
    H=zeros (1,n);   % high frequency component for
    i=1:n
        L (i) = (f (2*i-1) +f (2*i))/sqrt (2);
        H (i) = (f (2*i-1)-F (2*i))/sqrt (2);
    End
    

3. Analysis of experimental results