Main Content

isbiorthwfb

Determine if filter bank is biorthogonal wavelet filter bank

Since R2022b

    Description

    tf = isbiorthwfb(LoR,LoD) returns true if the two-channel filter bank formed from the lowpass filters LoR and LoD satisfy the necessary and sufficient conditions to be a two-channel biorthogonal perfect reconstruction (PR) wavelet filter bank. isbiorthwfb forms the dual highpass (wavelet) filters using the qmf function:

    • HiD = qmf(LoR)

    • HiR = qmf(LoD)

    For a list of the necessary and sufficient conditions that the lowpass and highpass filters must satisfy, see Biorthogonal Perfect Reconstruction Wavelet Filter Bank.

    tf = isbiorthwfb(LoR,LoD,HiR,HiD) uses the four filters LoR, LoD, HiR, and HiD to determine whether the four filters jointly satisfy the necessary and sufficient conditions to be a two-channel biorthogonal PR wavelet filter bank.

    tf = isbiorthwfb(___,Tolerance=tol) uses the positive real scalar tolerance tol to determine whether the filters satisfy the necessary and sufficient conditions to be a two-channel biorthogonal PR wavelet filter bank.

    example

    [tf,checks] = isbiorthwfb(___) returns a table with all orthogonality checks.

    Examples

    collapse all

    Use wfilters to obtain the biorthogonal spline wavelet filters with 3 vanishing moments in the analysis filters and 1 vanishing moment in the synthesis filters. The sum of the coefficients in each lowpass filter equals 2.

    [LoD,HiD,LoR,HiR] = wfilters("bior3.1");
    sum(LoD)-sqrt(2)
    ans = 2.2204e-16
    
    sum(LoR)-sqrt(2)
    ans = 2.2204e-16
    

    Test the biorthogonality of the filters.

    [tf,checks] = isbiorthwfb(LoR,LoD,HiR,HiD)
    tf = logical
       1
    
    
    checks=7×3 table
                                                           Pass-Fail    Maximum Error    Test Tolerance
                                                           _________    _____________    ______________
    
        Dual filter lengths correct                          pass                 0                 0  
        Filter sums                                          pass        2.2204e-16        1.4901e-08  
        Zero lag lowpass dual filter cross-correlation       pass        2.2204e-16        1.4901e-08  
        Zero lag highpass dual filter cross-correlation      pass        2.2204e-16        1.4901e-08  
        Even lag lowpass dual filter cross-correlation       pass                 0        1.4901e-08  
        Even lag highpass dual filter cross-correlation      pass                 0        1.4901e-08  
        Even lag lowpass-highpass cross-correlation          pass                 0        1.4901e-08  
    
    

    Use biorwavf to obtain just the lowpass analysis and synthesis filters of the same wavelet. The sum of the coefficients in each filter equals 1.

    [df,rf] = biorwavf("bior3.1");
    sum(df)
    ans = 1
    
    sum(rf)
    ans = 1
    

    Test the biorthogonality of the filters.

    [tf,checks] = isbiorthwfb(rf,df)
    tf = logical
       1
    
    
    checks=7×3 table
                                                           Pass-Fail    Maximum Error    Test Tolerance
                                                           _________    _____________    ______________
    
        Dual filter lengths correct                          pass                 0                 0  
        Filter sums                                          pass        2.2204e-16        1.4901e-08  
        Zero lag lowpass dual filter cross-correlation       pass        2.2204e-16        1.4901e-08  
        Zero lag highpass dual filter cross-correlation      pass        2.2204e-16        1.4901e-08  
        Even lag lowpass dual filter cross-correlation       pass                 0        1.4901e-08  
        Even lag highpass dual filter cross-correlation      pass                 0        1.4901e-08  
        Even lag lowpass-highpass cross-correlation          pass                 0        1.4901e-08  
    
    

    Input Arguments

    collapse all

    Lowpass filters, specified as a pair of real-valued vectors. One vector is a lowpass analysis filter, and the other vector is a lowpass synthesis filter. LoR and LoD are not required to have equal or even length. isbiorthwfb equalizes the lengths internally using biorfilt. LoR and LoD should sum to 1 or √2.

    Data Types: single | double

    Highpass filters, specified as a pair of real-valued vectors. isbiorthwfb assumes that the two pairs of vectors LoRHiR and LoDHiD form dual filter pairs.

    Data Types: single | double

    Tolerance used in the filter bank checks, specified as a positive real scalar.

    Output Arguments

    collapse all

    True or false result, returned as a 1 or 0 of data type logical. The isbiorthwfb function returns a 1 if the filters satisfy all the conditions listed in Biorthogonal Perfect Reconstruction Wavelet Filter Bank within the specified tolerance.

    Biorthogonality checks, returned as a table. The table shows pass or fail for each check as well as the maximum error and specified test tolerance where applicable. A test tolerance of 0 indicates that the check is a logical pass or fail.

    More About

    collapse all

    Biorthogonal Perfect Reconstruction Wavelet Filter Bank

    The lowpass and highpass analysis filters G˜ and H˜, respectively, and lowpass and highpass synthesis filters G and H, respectively, form a biorthogonal perfect reconstruction (PR) wavelet filter bank if the filters satisfy certain conditions. This is a diagrammatic representation of the two-channel filter bank.

    A two-channel filter bank. Pass input data X through two analysis filters and decimate by a factor of two. Upsample by two and pass through two synthesis filters. Combine to recover the input.

    Here, G˜(n)=(1)nH(1n) and G(n)=(1)nH˜(1n).

    The filters G˜, H˜,, G, and H, form a biorthogonal PR wavelet filter bank if the following conditions are satisfied.

    • Dual filter lengths correct — The length of G˜ equals the length of H,, and the length of G equals the length of H˜,.

    • Filter sums — For both lowpass filters, the sum of the coefficients equals √2. For both highpass filters, the sum of the coefficients equals 0.

    • Zero lag lowpass dual filter cross-correlation — The zero lag cross-correlation of the lowpass filter G and its dual equals 1: ng˜(n)g(n)=1

    • Zero lag highpass dual filter cross-correlation — The zero lag cross-correlation of the highpass filter H, and its dual equals 1: nh˜(n)h(n)=1

    • Even lag lowpass dual filter cross-correlation — The even nonzero lag cross-correlation of the lowpass filter and its dual equals 0: ng˜(n)g(n+2k)=0fork0.

    • Even lag highpass dual filter cross-correlation — The even nonzero lag cross-correlation of the highpass filter and its dual equals 0 nh˜(n)h(n+2k)=0fork0.

    • Even lag lowpass-highpass cross-correlation — The even lag cross-correlation of the lowpass and dual highpass filters equals 0. Similarly, the even lag cross-correlation of the highpass and dual lowpass filters equals 0: ng˜(n)h(n+2k)=nh˜(n)g(n+2k)=0

    References

    [1] Strang, Gilbert, and Truong Nguyen. Wavelets and Filter Banks. Rev. ed. Wellesley, Mass: Wellesley-Cambridge Press, 1997.

    [2] Burrus, C. S., Ramesh A. Gopinath, and Haitao Guo. Introduction to Wavelets and Wavelet Transforms: A Primer. Upper Saddle River, N.J: Prentice Hall, 1998.

    Extended Capabilities

    C/C++ Code Generation
    Generate C and C++ code using MATLAB® Coder™.

    Version History

    Introduced in R2022b