Tree-based majorize-maximize algorithm for compressed sensing with sparse-tree prior

Minh N. Do; Chinh N.H. La

doi:10.1109/CAMSAP.2007.4497982

Tree-based majorize-maximize algorithm for compressed sensing with sparse-tree prior

Minh N. Do, Chinh N.H. La

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Recent studies have shown that sparse representation can be used effectively as a prior in linear inverse problems. However, 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 this, named sparse-tree, prior for linear inverse problems with limited numbers of measurements. In particular, we present the tree-based majorize-maximize (TMM) algorithm for signal reconstruction in this setting. Our numerical results show that TMM provides significantly better reconstruction quality compared to the majorize-maximize (MM) algorithm that relies only on the sparse prior.

Original language	English (US)
Title of host publication	2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP
Pages	129-132
Number of pages	4
DOIs	https://doi.org/10.1109/CAMSAP.2007.4497982
State	Published - 2007
Event	2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP - St. Thomas, Virgin Islands, U.S. Duration: Dec 12 2007 → Dec 14 2007

Publication series

Name	2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP

Other

Other	2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP
Country/Territory	Virgin Islands, U.S.
City	St. Thomas
Period	12/12/07 → 12/14/07

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Control and Systems Engineering
Electrical and Electronic Engineering

Online availability

10.1109/CAMSAP.2007.4497982

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Do, M. N., & La, C. N. H. (2007). Tree-based majorize-maximize algorithm for compressed sensing with sparse-tree prior. In 2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP (pp. 129-132). Article 4497982 (2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP). https://doi.org/10.1109/CAMSAP.2007.4497982

Tree-based majorize-maximize algorithm for compressed sensing with sparse-tree prior. / Do, Minh N.; La, Chinh N.H.
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP. 2007. p. 129-132 4497982 (2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Do, MN & La, CNH 2007, Tree-based majorize-maximize algorithm for compressed sensing with sparse-tree prior. in 2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP., 4497982, 2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP, pp. 129-132, 2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP, St. Thomas, Virgin Islands, U.S., 12/12/07. https://doi.org/10.1109/CAMSAP.2007.4497982

Do MN, La CNH. Tree-based majorize-maximize algorithm for compressed sensing with sparse-tree prior. In 2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP. 2007. p. 129-132. 4497982. (2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP). doi: 10.1109/CAMSAP.2007.4497982

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Tree-based majorize-maximize algorithm for compressed sensing with sparse-tree prior

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