Hermitian wavelet explained
Hermitian wavelets are a family of discrete and continuous wavelets used in the constant and discrete Hermite wavelet transforms. The
Hermitian wavelet is defined as the normalized
derivative of a
Gaussian distribution for each positive
:
[1] where
denotes the
probabilist's Hermite polynomial. Each normalization coefficient
is given by
The function
\Psi\inL\rho,(-infty,infty)
is said to be an admissible Hermite wavelet if it satisfies the admissibility condition:
[2]
where
are the terms of the
Hermite transform of
.
In computer vision and image processing, Gaussian derivative operators of different orders are frequently used as a basis for expressing various types of visual operations; see scale space and N-jet.[3]
Examples
The first three derivatives of the Gaussian function with
:
are:
and their
norms
\lVertf'\rVert=\sqrt{2}/2,\lVertf''\rVert=\sqrt{3}/2,\lVertf(3)\rVert=\sqrt{30}/4
.
Normalizing the derivatives yields three Hermitian wavelets:
See also
Hermitian wavelet
External links
Notes and References
- Brackx. F.. De Schepper. H.. De Schepper. N.. Sommen. F.. 2008-02-01. Hermitian Clifford-Hermite wavelets: an alternative approach. Bulletin of the Belgian Mathematical Society, Simon Stevin. 15. 1. 10.36045/bbms/1203692449. 1370-1444. free.
- 2020 . Continuous and Discrete Wavelet Transforms Associated with Hermite Transform . International Journal of Analysis and Applications . 10.28924/2291-8639-18-2020-531. free .
- Book: Wiley Encyclopedia of Computer Science and Engineering . 2007-03-15 . Wiley . 978-0-471-38393-2 . Wah . Benjamin W. . 1 . en . 10.1002/9780470050118.ecse609.