Paper
13 November 2003 TBB (true best base) searching method and its applications
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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.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hai-Wen Chen and Teresa Olson "TBB (true best base) searching method and its applications", Proc. SPIE 5207, Wavelets: Applications in Signal and Image Processing X, (13 November 2003); https://doi.org/10.1117/12.502397
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KEYWORDS
Wavelets

Associative arrays

Feature extraction

Signal to noise ratio

Discrete wavelet transforms

Electronic filtering

Time-frequency analysis

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