ICIP 2006, Atlanta, GA
 

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Paper Detail

Paper:TA-L6.6
Session:Signal/Image Reconstruction from Sparse Measurements
Time:Tuesday, October 10, 11:40 - 12:00
Presentation: Special Session Lecture
Topic: Special Sessions: Signal/image reconstruction from sparse measurements
Title: TREE-BASED ORTHOGONAL MATCHING PURSUIT ALGORITHM FOR SIGNAL RECONSTRUCTION
Authors: Chinh La; University of Illinois at Urbana-Champaign 
 Minh Do; University of Illinois at Urbana-Champaign 
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. piecewisesmooth 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 Treebased Orthogonal Matching Pursuit (TOMP) is shown to provide significant better reconstruction compared to methods that only use sparse representation assumption