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Proceedings Paper

Optimized fusion method based on adaptation of the RMS time-frequency criterion for simultaneous compression and encryption of multiple images
Author(s): M. Aldossari; A. Alfalou; C. Brosseau
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Paper Abstract

An extension of the recently proposed method of simultaneous compression and encryption of multiple images [Opt. Lett. 35, 1914-1916 (2010)] is developed. This analysis allows us to find a compromise between compression rate and quality of the reconstructed images for target detection applications. This spectral compression method can significantly reduce memory size and can be easily implemented with a VanderLugt correlator (VLC). For that purpose, we determine the size of the useful spectra for each target image by exploiting the root-mean-square time-frequency criterion. This parameter is used to determine the allowed area of each target image within the compressed spectrum. Moreover, this parameter is adapted in order to minimize overlapping between the different spectra. For that purpose we add a shift function adapted to each spectra. Finally, the spectra are merged together by making use of a segmentation criterion. The latter compares the local energy relative to each pixel for each spectrum. Furthermore, it optimizes assignment of the considered pixel by taking into account the adjacent areas to the considered pixel. This permits to avoid the presence of isolated areas and small sized areas (less than 10 pixels). In this paper, we analyse and optimize the shift function needed to separate the different spectra. We use mean square error (MSE) for comparing compression rates. A series of tests with several video sequences show the benefit of this shift function on the quality of reconstructed images and compression rate.

Paper Details

Date Published: 29 April 2013
PDF: 7 pages
Proc. SPIE 8748, Optical Pattern Recognition XXIV, 87480B (29 April 2013); doi: 10.1117/12.2014465
Show Author Affiliations
M. Aldossari, ISEN Brest (France)
A. Alfalou, ISEN Brest (France)
C. Brosseau, Univ. Européenne de Bretagne, Univ. de Brest, Lab-STICC, CNRS (France)

Published in SPIE Proceedings Vol. 8748:
Optical Pattern Recognition XXIV
David Casasent; Tien-Hsin Chao, Editor(s)

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