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Authors: George Tzagkarakis 1 ; Arnaud Woiselle 2 ; Panagiotis Tsakalides 3 and Jean-Luc Starck 1

Affiliations: 1 SEDI-SAp and Service d’Astrophysique, France ; 2 Sagem Défense Sécurité, France ; 3 Foundation for Research & Technology - Hellas (FORTH), Greece

Keyword(s): Compressive Video Sensing, Lightweight Remote Imaging Systems.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Coding and Compression ; Image Enhancement and Restoration ; Image Formation and Preprocessing

Abstract: Lightweight remote imaging systems have been increasingly used in surveillance and reconnaissance. Nevertheless, the limited power, processing and bandwidth resources is a major issue for the existing solutions, not well addressed by the standard video compression techniques. On the one hand, the MPEGx family achieves a balance between the reconstruction quality and the required bit-rate by exploiting potential intra- and interframe redundancies at the encoder, but at the cost of increased memory and processing demands. On the other hand, the M-JPEG approach consists of a computationally efficient encoding process, with the drawback of resulting in much higher bit-rates. In this paper, we cope with the growing compression ratios, required for all remote imaging applications, by exploiting the inherent property of compressive sensing (CS), acting simultaneously as a sensing and compression framework. The proposed compressive video sensing (CVS) system incorporates the advantages of a very simple CS-based encoding process, while putting the main computational burden at the decoder combining the efficiency of a motion compensation procedure for the extraction of inter-frame correlations, along with an additional super-resolution step to enhance the quality of reconstructed frames. The experimental results reveal a significant improvement of the reconstruction quality when compared with M-JPEG, at equal or even lower bit-rates. (More)

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Paper citation in several formats:
Tzagkarakis, G.; Woiselle, A.; Tsakalides, P. and Starck, J. (2012). DESIGN OF A COMPRESSIVE REMOTE IMAGING SYSTEM COMPENSATING A HIGHLY LIGHTWEIGHT ENCODING WITH A REFINED DECODING SCHEME. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2012) - Volume 2: VISAPP; ISBN 978-989-8565-03-7; ISSN 2184-4321, SciTePress, pages 46-55. DOI: 10.5220/0003842400460055

@conference{visapp12,
author={George Tzagkarakis. and Arnaud Woiselle. and Panagiotis Tsakalides. and Jean{-}Luc Starck.},
title={DESIGN OF A COMPRESSIVE REMOTE IMAGING SYSTEM COMPENSATING A HIGHLY LIGHTWEIGHT ENCODING WITH A REFINED DECODING SCHEME},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2012) - Volume 2: VISAPP},
year={2012},
pages={46-55},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003842400460055},
isbn={978-989-8565-03-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2012) - Volume 2: VISAPP
TI - DESIGN OF A COMPRESSIVE REMOTE IMAGING SYSTEM COMPENSATING A HIGHLY LIGHTWEIGHT ENCODING WITH A REFINED DECODING SCHEME
SN - 978-989-8565-03-7
IS - 2184-4321
AU - Tzagkarakis, G.
AU - Woiselle, A.
AU - Tsakalides, P.
AU - Starck, J.
PY - 2012
SP - 46
EP - 55
DO - 10.5220/0003842400460055
PB - SciTePress