Signal reconstruction using sparse tree representation

Signal reconstruction using sparse tree representation (2005)

by Chinh La , Minh N. Do

Venue:	in Proc. Wavelets XI at SPIE Optics and Photonics
Citations:	23 - 1 self

Datum	Value	Source
TITLE	Signal reconstruction using sparse tree representation	INFERENCE
AUTHOR NAME	Chinh La	SVM HeaderParse 0.2
AUTHOR AFFIL	Department of Electrical and Computer Engineering; University of Illinois at Urbana-Champaign	SVM HeaderParse 0.2
AUTHOR NAME	Minh N. Do	SVM HeaderParse 0.2
AUTHOR AFFIL	Department of Electrical and Computer Engineering; University of Illinois at Urbana-Champaign	SVM HeaderParse 0.2
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. 1.	SVM HeaderParse 0.2
YEAR	2005	INFERENCE
VENUE	in Proc. Wavelets XI at SPIE Optics and Photonics	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
VOLUME	5914	INFERENCE
CITATIONS	13 found	ParsCit 1.0