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Paper data
Local Optimization of Index Assignments for Multiple Description Coding

Cardinal Jean, Université Libre de Bruxelles
Elloumi Sourour, CEDRIC-CNAM
Labbé Martine, Université Libre de Bruxelles

Page numbers in the proceedings:
Volume I pp 269-272

Source Coding

Paper abstract
Index assignment problems are central to many joint source-channel coding methods and generally require a lot of computational power. We study the optimization of index assignment matrices for the multiple description coding problem. Index assignment matrices are used at the quantization step and provide a conceptually simple and fast alternative to multiply descriptive transform methods. We describe two novel local optimization algorithms using a bipartite matching procedure to locally minimize the expected mean squared error. We provide experimental results on various codebooks as well as a comparison with a previously published optimization algorithm.

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