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NUMERICAL EVALUATION OF SAMPLING BOUNDS FOR NEAR-OPTIMAL RECONSTRUCTION IN COMPRESSED SENSING
 

Summary: NUMERICAL EVALUATION OF SAMPLING BOUNDS FOR NEAR-OPTIMAL
RECONSTRUCTION IN COMPRESSED SENSING
Yoann Le Montagner1,2
, Marcio Marim1,2
, Elsa Angelini2
, Jean-Christophe Olivo-Marin1
1
Institut Pasteur, Unité d'Analyse d'Images Quantitative CNRS URA 2582, F-75015 Paris
2
Institut Télécom, Télécom ParisTech CNRS LTCI, F-75013 Paris
ABSTRACT
In this paper, we propose an empirical review of the conditions un-
der which the compressed sensing framework allows to achieve ex-
act image reconstruction. After a short presentation of the theoret-
ical results related to this subject, we investigate the relevance and
the limits of these theoretical results through several numerical re-
constructions of some benchmark images. In particular, we discuss
quantitative and qualitative artifacts that affect the reconstructed im-
age when reducing the number of measurements in the Fourier do-
main. Finally, we conclude our study by extending our results to

  

Source: Angelini, Elsa -Département Traitement du Signal et des Images, Telecom ParisTech

 

Collections: Engineering; Biology and Medicine