Efficient deterministic compressed sensing for images with chirps and reed-muller codes

Kangyu Ni; Somantika Datta; Prasun Mahanti; Svetlana Roudenko; Douglas Cochran

doi:10.1137/100808794

Efficient deterministic compressed sensing for images with chirps and reed-muller codes

Kangyu Ni, Somantika Datta, Prasun Mahanti, Svetlana Roudenko, Douglas Cochran

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

A recent approach to compressed sensing using deterministic sensing matrices formed from discrete frequency-modulated chirps or from Reed-Muller codes is extended to support efficient deterministic reconstruction of signals that are much less sparse than envisioned in the original work. In particular, this allows the application of this approach in imaging. The reconstruction algorithm developed for images incorporates several new elements to improve computational complexity and reconstruction fidelity in this application regime.

Original language	English (US)
Pages (from-to)	931-953
Number of pages	23
Journal	SIAM Journal on Imaging Sciences
Volume	4
Issue number	3
DOIs	https://doi.org/10.1137/100808794
State	Published - 2011

Keywords

Compressed sensing
Frequency-modulated chirps
Image reconstruction
Medical imaging
Reed-muller codes

ASJC Scopus subject areas

General Mathematics
Applied Mathematics

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10.1137/100808794

Cite this

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abstract = "A recent approach to compressed sensing using deterministic sensing matrices formed from discrete frequency-modulated chirps or from Reed-Muller codes is extended to support efficient deterministic reconstruction of signals that are much less sparse than envisioned in the original work. In particular, this allows the application of this approach in imaging. The reconstruction algorithm developed for images incorporates several new elements to improve computational complexity and reconstruction fidelity in this application regime.",

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AU - Roudenko, Svetlana

AU - Cochran, Douglas

PY - 2011

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AB - A recent approach to compressed sensing using deterministic sensing matrices formed from discrete frequency-modulated chirps or from Reed-Muller codes is extended to support efficient deterministic reconstruction of signals that are much less sparse than envisioned in the original work. In particular, this allows the application of this approach in imaging. The reconstruction algorithm developed for images incorporates several new elements to improve computational complexity and reconstruction fidelity in this application regime.

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KW - Image reconstruction

KW - Medical imaging

KW - Reed-muller codes

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Efficient deterministic compressed sensing for images with chirps and reed-muller codes

Abstract

Keywords

ASJC Scopus subject areas

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