hanscalf

Han real orthogonal scaling filters with sum and linear-phase moments

Since R2022b

Syntax

scalf = hanscalf(wname)

Description

scalf = hanscalf(wname) returns the Han real-valued orthogonal scaling filter corresponding to wname.

Examples

Han Real Orthogonal Wavelet

Obtain the scaling filter corresponding to the Han real orthogonal wavelet with five sum rules and five linear-phase moments.

scalf = hanscalf("han5.5");

Use orthfilt to obtain the scaling and wavelet filters corresponding to the wavelet.

[LoD,HiD,LoR,HiR] = orthfilt(scalf);

Confirm the filters form an orthonormal perfect reconstruction wavelet filter bank.

[tf,checks] = isorthwfb(LoD)

tf = logical
   1

checks=7×3 table
                                          Pass-Fail    Maximum Error    Test Tolerance
                                          _________    _____________    ______________

    Equal-length filters                    pass                 0                 0  
    Even-length filters                     pass                 0                 0  
    Unit-norm filters                       pass        1.2168e-13        1.4901e-08  
    Filter sums                             pass        2.1645e-13        1.4901e-08  
    Even and odd downsampled sums           pass        1.0836e-13        1.4901e-08  
    Zero autocorrelation at even lags       pass        1.2484e-13        1.4901e-08  
    Zero crosscorrelation at even lags      pass        2.1922e-17        1.4901e-08  

Create two discrete wavelet transform filter banks, one using the Han wavelet, and the other using the Haar wavelet. Specify a single level of decomposition for both filter banks. Plot the one-sided magnitude frequency responses of both filter banks. The Han wavelet has a larger frequency separation between the wavelet and scaling filters than the Haar wavelet.

fbHan = dwtfilterbank(Wavelet="han5.5",Level=1);
fbHaar = dwtfilterbank(Wavelet="haar",Level=1);
freqz(fbHan)

figure
freqz(fbHaar)

Input Arguments

wname — Han scaling filter

"hanSR.LP"

Han scaling filter, specified as "hanSR.LP", where SR is the number of sum rules, and LP is the number of linear-phase moments. wname can be "han2.3", "han3.3", "han4.5", or "han5.5". For information on the filter properties, see Han Real Orthogonal Scaling Filters.

Output Arguments

scalf — Scaling filter

vector

Scaling filter corresponding to wname, returned as a vector. scalf should be used in conjunction with orthfilt to obtain scaling and wavelet filters with the proper normalization.

Data Types: double

More About

Han Real Orthogonal Scaling Filters

Han filters are characterized by their order of sum rules, linear-phase moments, and phase. This table lists the filter specifications for the valid values of wname.

wname	Order of Sum Rules	Number of Linear-Phase Moments	Normalized Variance of Filter Impulse Response	Frequency Separation Between Scaling and Wavelet Filter	Length
"han2.3"	2	3	0.465	0.8156	6
"han2.3"	2	3	0.426	0.8540	8
"han4.5"	4	5	0.488	0.8563	10
"han5.5"	5	5	0.530	0.8867	14

Frequency separation is a number between 0 and 1, where 0 indicates the filters are perfectly matched and 1 indicates they are perfectly separated in frequency. As a point of reference, the Haar ("db1") wavelet filter has the smallest normalized variance of all wavelet filters with 0.25 and poorest frequency separation with 0.666. An example of a scaling and wavelet filter pair with a relatively large frequency separation is the Fejér-Korovkin ("fk22") 22-coefficient filter with a value of 0.9522.

References

[1] Han, Bin. “Wavelet Filter Banks.” In Framelets and Wavelets: Algorithms, Analysis, and Applications, 92–98. Applied and Numerical Harmonic Analysis. Cham, Switzerland: Birkhäuser, 2017. https://doi.org/10.1007/978-3-319-68530-4_2.

Extended Capabilities

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

Version History

Introduced in R2022b