Scalable Multiple-Description Image Coding Based on Embedded Quantization

Augustin Gavrilescu, Fabio Verdicchio, Adrian Munteanu, Ingrid Moerman, Jan Cornelis, Peter Schelkens

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


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.
Original languageEnglish
Article number81813
Number of pages11
JournalEURASIP Journal of Image and Video Processing
Publication statusPublished - Jan 2007


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