Share Email Print

Proceedings Paper

Signal reconstruction using sparse tree representations
Author(s): Chinh La; Minh N. Do
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Recent studies in linear inverse problems have recognized the sparse representation of unknown signal in a certain basis as an useful and effective prior information to solve those problems. In many multiscale bases (e.g. wavelets), signals of interest (e.g. piecewise-smooth signals) not only have few significant coefficients, but also those significant coefficients are well-organized in trees. We propose to exploit the tree-structured sparse representation as additional prior information for linear inverse problems with limited numbers of measurements. We present numerical results showing that exploiting the sparse tree representations lead to better reconstruction while requiring less time compared to methods that only assume sparse representations.

Paper Details

Date Published: 17 September 2005
PDF: 11 pages
Proc. SPIE 5914, Wavelets XI, 59140W (17 September 2005); doi: 10.1117/12.621064
Show Author Affiliations
Chinh La, Univ. of Illinois at Urbana-Champaign (United States)
Minh N. Do, Univ. of Illinois at Urbana-Champaign (United States)

Published in SPIE Proceedings Vol. 5914:
Wavelets XI
Manos Papadakis; Andrew F. Laine; Michael A. Unser, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?