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 :
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