Share Email Print
cover

Proceedings Paper

Learning optimal wavelets from overcomplete representations
Author(s): Hamid Eghbalnia; Amir H. Assadi
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Efficient and robust representation of signals has been the focus of a number of areas of research. Wavelets represent one such representation scheme that enjoys desirable qualitites such as time-frequency localization. Once the Mother wavelet has been selected, other wavelets can be generated as translated and dilated versions of the Mother wavelet in the 1D case. In the 2D case tensor product of two 1D wavelets is the most often used transform. Over complete representation of wavelets has proved to be of great advantage, both in sparse coding of complex scenes and multi-media data compression. On the other hand over completeness raises a number of technical difficulties for robust computation and systematic generalization of constructions beyond their original application domains.

Paper Details

Date Published: 4 December 2000
PDF: 8 pages
Proc. SPIE 4119, Wavelet Applications in Signal and Image Processing VIII, (4 December 2000); doi: 10.1117/12.408612
Show Author Affiliations
Hamid Eghbalnia, Univ. of Wisconsin/Madison (United States)
Amir H. Assadi, Univ. of Wisconsin/Madison (United States)


Published in SPIE Proceedings Vol. 4119:
Wavelet Applications in Signal and Image Processing VIII
Akram Aldroubi; Andrew F. Laine; Michael A. Unser, Editor(s)

© SPIE. Terms of Use
Back to Top