Distributed Lossy Source Coding Using Real-Number Codes

descriptionPublicationkeyboard_double_arrow_right Article , Preprint , Conference object 01 Sep 2012Embargo end date: 01 Jan 2011Publisher:IEEEJournal:2012 IEEE Vehicular Technology Conference (VTC Fall)Funded by:NSERC | unidentified

Authors: Mojtaba Vaezi; Fabrice Labeau;

doi: 10.1109/vtcfall.2012.6399216 , 10.48550/arxiv.1111.0654

arXiv: 1111.0654

Distributed Lossy Source Coding Using Real-Number Codes

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Abstract

We show how real-number codes can be used to compress correlated sources, and establish a new framework for lossy distributed source coding, in which we quantize compressed sources instead of compressing quantized sources. This change in the order of binning and quantization blocks makes it possible to model correlation between continuous-valued sources more realistically and correct quantization error when the sources are completely correlated. The encoding and decoding procedures are described in detail, for discrete Fourier transform (DFT) codes. Reconstructed signal, in the mean squared error sense, is seen to be better than that in the conventional approach.

5 pages, 5 figures, to appear in VTC_Fall 2012

Related Organizations

McGill University
Canada

Keywords

Computer Science - Networking and Internet Architecture, Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition

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