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EURASIP Journal on Image and Video Processing
EURASIP Journal on Image and Video Processing Cover Image
  • Research Article
  • Open Access

Scalable Multiple-Description Image Coding Based on Embedded Quantization

  • 1Email author,
  • 1,
  • 1,
  • 2,
  • 1 and
  • 1
EURASIP Journal on Image and Video Processing20072007:081813

https://doi.org/10.1155/2007/81813

©  Augustin I. Gavrilescu et al. 2007

  • Received: 14 August 2006
  • Accepted: 5 January 2007
  • Published:

Abstract

Scalable multiple-description (MD) coding allows for fine-grain rate adaptation as well as robust coding of the input source. In this paper, we present a new approach for scalable MD coding of images, which couples the multiresolution nature of the wavelet transform with the robustness and scalability features provided by embedded multiple-description scalar quantization (EMDSQ). Two coding systems are proposed that rely on quadtree coding to compress the side descriptions produced by EMDSQ. The proposed systems are capable of dynamically adapting the bitrate to the available bandwidth while providing robustness to data losses. Experiments performed under different simulated network conditions demonstrate the effectiveness of the proposed scalable MD approach for image streaming over error-prone channels.

Keywords

  • Network Condition
  • Scalability Feature
  • Rate Adaptation
  • Data Loss
  • Simulated Network

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Authors’ Affiliations

(1)
Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB) and Interdisciplinary Institute for Broadband Technology (IBBT), Pleinlaan 2, Brussels, 1050, Belgium
(2)
Department of Information Technology (INTEC), Universiteit Gent (UGent) and Interdisciplinary Institute for Broadband Technology (IBBT), St.-Pietersnieuwstraat 41, Ghent, 9000, Belgium

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Copyright

© Augustin I. Gavrilescu et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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