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- W2168313063 abstract "The optimal joint decoder utilizing NLIVQ (nonlinear interpolative vector quantization) introduced by Gersho [1990] results in vector quantizers which have reduced encoding complexity at the expense of coding performance loss due to the inferiority of their space-filling property. We show a method of improving a high resolution NLIVQ codebook by partitioning its cells in such a way that the resulting lower resolution codebook consists of cells with better space-filling properties. The resolution reduction method is also extended to the case where the quantizer indices are entropy-constrained. From the simulations it is seen that the unconstrained and constrained entropy versions of the proposed vector quantizer have comparable performance to vector quantizers designed by LEG and ECVQ algorithms." @default.
- W2168313063 created "2016-06-24" @default.
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- W2168313063 date "2002-11-19" @default.
- W2168313063 modified "2023-09-26" @default.
- W2168313063 title "Improving the performance of optimal joint decoding" @default.
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- W2168313063 doi "https://doi.org/10.1109/icip.1995.529052" @default.
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