DocumentCode
248142
Title
Sparse image recovery using compressed sensing over finite alphabets
Author
Bioglio, Valerio ; Coluccia, Giulio ; Magli, Enrico
Author_Institution
Dipt. di Elettron. e Telecomun., Politec. di Torino, Turin, Italy
fYear
2014
fDate
27-30 Oct. 2014
Firstpage
1287
Lastpage
1291
Abstract
In this paper we present F2 OMP, a recovery algorithm for Compressed Sensing over finite fields. Classical recovery algorithms do not exploit the fact that a signal may belong to a finite alphabet, while we show that this information can lead to more efficient reconstruction algorithms. As an application, we use the proposed algorithm to recover sparse grayscale images, showing that performing CS operation over a finite field can outperform classical recovery algorithms from visual quality, memory occupation and complexity point of view.
Keywords
compressed sensing; image reconstruction; CS operation; F2OMP; compressed sensing; finite alphabets; memory occupation; reconstruction algorithms; recovery algorithms; sparse grayscale images; sparse image recovery; visual quality; Compressed sensing; Image reconstruction; Loss measurement; Matching pursuit algorithms; Sensors; Sparse matrices; Vectors; Compressed Sensing; Finite Fields; Orthogonal Matching Pursuit; Sparse Image Recovery;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location
Paris
Type
conf
DOI
10.1109/ICIP.2014.7025257
Filename
7025257
Link To Document