Title: Image compression-based multiple description transform coding using NSCT and OMP approximation

Authors: Amina Naimi; Kamel Belloulata

Addresses: TTNS Laboratory, Department of Telecommunications, Faculty of Electrical Engineering, Djillali Liabes University of Sidi Bel Abbes, Algeria ' RCAM Laboratory, Department of Telecommunications, Faculty of Electrical Engineering, Djillali Liabes University of Sidi Bel Abbes, Algeria

Abstract: In this paper, we present a novel multiple description transform image coding architecture, which uses an attractive transform called non-subsampled contourlet transform (NSCT). It combines NSCT and orthogonal matching pursuit algorithm (OMP) to give a sparse representation of images, aiming at solving the compression problem due to the redundancy property of NSCT. In this way, OMP turns to give a solution to remove the redundancies. We evaluate the performance of our image coder in the case of four descriptions that are dispatched over different channels. The experimentations show that the proposed method is efficient and the potential using NSCT than DWT in multiple description image coding, is evaluated by PSNR in each case of packet loss, where every description can reconstruct the image with acceptable fidelity, the later is much better if all descriptions are available.

Keywords: multiple description coding; MDC; non-subsampled contourlet transform; NSCT; discrete wavelet transform; DWT; orthogonal matching pursuit; OMP.

DOI: 10.1504/IJCVR.2018.090015

International Journal of Computational Vision and Robotics, 2018 Vol.8 No.1, pp.42 - 57

Received: 27 Oct 2015
Accepted: 01 Mar 2016

Published online: 06 Oct 2017 *

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