Paper
17 September 2005 Signal reconstruction using sparse tree representations
Chinh La, Minh N. Do
Author Affiliations +
Proceedings Volume 5914, Wavelets XI; 59140W (2005) https://doi.org/10.1117/12.621064
Event: Optics and Photonics 2005, 2005, San Diego, California, United States
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.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chinh La and Minh N. Do "Signal reconstruction using sparse tree representations", Proc. SPIE 5914, Wavelets XI, 59140W (17 September 2005); https://doi.org/10.1117/12.621064
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Cited by 96 scholarly publications and 1 patent.
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KEYWORDS
Signal to noise ratio

Wavelets

Reconstruction algorithms

Inverse problems

Chemical species

Solids

Wavelet transforms

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