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Central Decoding for Multiple Description Codes based on Domain Partitioning

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Bibliographic Details
Title: Central Decoding for Multiple Description Codes based on Domain Partitioning
Authors: Spiertz, M., Rusert, T.
Source: Acta Polytechnica; Vol 46 No 4 (2006) ; Acta Polytechnica; Vol. 46 No. 4 (2006) ; 1805-2363
Publisher Information: Czech Technical University in Prague
Publication Year: 2006
Collection: CTU Open Journal Systems (Czech Technical University, Prague / České vysoké učení technické v Praze)
Subject Terms: multiple description coding, domain based, scalar quantization, reconstruction, central decoder
Description: Multiple Description Codes (MDC) can be used to trade redundancy against packet loss resistance for transmitting data over lossy diversity networks. In this work we focus on MD transform coding based on domain partitioning. Compared to Vaishampayan’s quantizer based MDC, domain based MD coding is a simple approach for generating different descriptions, by using different quantizers for each description. Commonly, only the highest rate quantizer is used for reconstruction. In this paper we investigate the benefit of using the lower rate quantizers to enhance the reconstruction quality at decoder side. The comparison is done on artificial source data and on image data.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
Relation: https://ojs.cvut.cz/ojs/index.php/ap/article/view/852/684; https://ojs.cvut.cz/ojs/index.php/ap/article/view/852
DOI: 10.14311/852
Availability: https://ojs.cvut.cz/ojs/index.php/ap/article/view/852
https://doi.org/10.14311/852
Rights: Copyright (c) 2015 Acta Polytechnica
Accession Number: edsbas.193DF521
Database: BASE
Description
Abstract:Multiple Description Codes (MDC) can be used to trade redundancy against packet loss resistance for transmitting data over lossy diversity networks. In this work we focus on MD transform coding based on domain partitioning. Compared to Vaishampayan’s quantizer based MDC, domain based MD coding is a simple approach for generating different descriptions, by using different quantizers for each description. Commonly, only the highest rate quantizer is used for reconstruction. In this paper we investigate the benefit of using the lower rate quantizers to enhance the reconstruction quality at decoder side. The comparison is done on artificial source data and on image data.
DOI:10.14311/852