Tree-based orthogonal matching pursuit algorithm for signal reconstruction

Chinh La, Minh N. Do

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 this sparse tree representation as additional prior information for linear inverse problems with limited numbers of measurements. In particular, our proposed algorithm named Tree-based Orthogonal Matching Pursuit (TOMP) is shown to provide significant better reconstruction compared to methods that only use sparse representation assumption.

Original languageEnglish (US)
Title of host publication2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings
Pages1277-1280
Number of pages4
DOIs
StatePublished - Dec 1 2006
Event2006 IEEE International Conference on Image Processing, ICIP 2006 - Atlanta, GA, United States
Duration: Oct 8 2006Oct 11 2006

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2006 IEEE International Conference on Image Processing, ICIP 2006
CountryUnited States
CityAtlanta, GA
Period10/8/0610/11/06

Keywords

  • Greedy algorithms
  • Inverse problems
  • Sparse representations
  • Tree structures
  • Tree-based orthogonal matching pursuit

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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  • Cite this

    La, C., & Do, M. N. (2006). Tree-based orthogonal matching pursuit algorithm for signal reconstruction. In 2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings (pp. 1277-1280). [4106770] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2006.312578