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Proceedings Paper

TBB (true best base) searching method and its applications
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Paper Abstract

The binary-tree best base (BTBB) searching method developed by Coifman and Wickerhauser 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 BTBB method. Based on this observation, we have developed the true best base (TBB) searching method - a new way to search the best base among a much larger set of orthogonal bases. In this paper, we show that considerable improvements in signal compression, de-noising, and time-frequency analysis can be achieved using the new TBB method. Furthermore, we show that the TBB method can be used as a searching engine to extract the local discriminant base (LDB) for feature extraction and signal/object classification, and we compare the performances of the LDBs extracted by the TBB and BTBB.

Paper Details

Date Published: 13 November 2003
PDF: 12 pages
Proc. SPIE 5207, Wavelets: Applications in Signal and Image Processing X, (13 November 2003); doi: 10.1117/12.502397
Show Author Affiliations
Hai-Wen Chen, Lockheed Martin Missiles and Fire Control (United States)
Teresa Olson, Lockheed Martin Missiles and Fire Control (United States)

Published in SPIE Proceedings Vol. 5207:
Wavelets: Applications in Signal and Image Processing X
Michael A. Unser; Akram Aldroubi; Andrew F. Laine, Editor(s)

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