Distributed transform coding via source-splitting

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dc.contributor.authorYahampath, Pradeepa
dc.date.accessioned2012-08-03T11:44:01Z
dc.date.available2012-08-03T11:44:01Z
dc.date.issued2012-04-05
dc.date.updated2012-08-03T11:44:01Z
dc.description.abstractAbstract Transform coding (TC) is one of the best known practical methods for quantizing high-dimensional vectors. In this article, a practical approach to distributed TC of jointly Gaussian vectors is presented. This approach, referred to as source-split distributed transform coding (SP-DTC), can be used to easily implement two terminal transform codes for any given rate-pair. The main idea is to apply source-splitting using orthogonal-transforms, so that only Wyner-Ziv (WZ) quantizers are required for compression of transform coefficients. This approach however requires optimizing the bit allocation among dependent sets of WZ quantizers. In order to solve this problem, a low-complexity tree-search algorithm based on analytical models for transform coefficient quantization is developed. A rate-distortion (RD) analysis of SP-DTCs for jointly Gaussian sources is presented, which indicates that these codes can significantly outperform the practical alternative of independent TC of each source, whenever there is a strong correlation between the sources. For practical implementation of SP-DTCs, the idea of using conditional entropy constrained (CEC) quantizers followed by Slepian-Wolf coding is explored. Experimental results obtained with SP-DTC designs based on both CEC scalar quantizers and CEC trellis-coded quantizers demonstrate that actual implementations of SP-DTCs can achieve RD performance close to the analytically predicted limits.
dc.description.versionPeer Reviewed
dc.identifier.citationEURASIP Journal on Advances in Signal Processing. 2012 Apr 05;2012(1):78
dc.identifier.doihttp://dx.doi.org/10.1186/1687-6180-2012-78
dc.identifier.urihttp://hdl.handle.net/1993/8147
dc.language.rfc3066en
dc.rightsopen accessen_US
dc.rights.holderPradeepa Yahampath et al.; licensee BioMed Central Ltd.
dc.titleDistributed transform coding via source-splitting
dc.typeJournal Article
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