New way to search for the best base in wavelet packets

Hai-Wen Chen; Teresa L. P. Olson

doi:10.1117/12.458745

8 March 2002 New way to search for the best base in wavelet packets

Hai-Wen Chen, Teresa L. P. Olson

Proceedings Volume 4738, Wavelet and Independent Component Analysis Applications IX; (2002) https://doi.org/10.1117/12.458745
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

The binary-tree best base searching method developed by Coifman and his colleagues is well known and widely used in wavelet packet applications. However, the requirement that the base vectors be chosen from either a parent or its directly related children in the binary-tree structure is a limitation because it doesn't search all possible orthogonal bases and therefore may not provide a optimal result. We have recently found that the set of all possible orthogonal bases in a wavelet packet is much larger than the set searched by the binary-tree method. Based on this observation, we have developed a new way to search the best base among the larger set of orthogonal bases. Preliminary results on 1D signals show that we can achieve considerable improvement in signal compression and feature extraction using the new method. This method can also be readily extended to 2D images for improved image compression, feature extraction, and object classification.

Citation Download Citation

Hai-Wen Chen and Teresa L. P. Olson "New way to search for the best base in wavelet packets", Proc. SPIE 4738, Wavelet and Independent Component Analysis Applications IX, (8 March 2002); https://doi.org/10.1117/12.458745

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available