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Entropy-Constrained Successively Refinable Scalar Quantization (1997)
| Venue: | Proc. IEEE Data Compression Conf |
| Citations: | 9 - 2 self |
BibTeX
@INPROCEEDINGS{Jafarkhani97entropy-constrainedsuccessively,
author = {Hamid Jafarkhani and Hugh Brunk and Nariman Farvardin},
title = {Entropy-Constrained Successively Refinable Scalar Quantization},
booktitle = {Proc. IEEE Data Compression Conf},
year = {1997},
pages = {250--259}
}
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Abstract
We study the design of entropy--constrained successively refinable scalar quantizers. We propose two algorithms to minimize the average distortion and design such a quantizer. We consider two sets of constraints on the entropy: (i) constraint on the average rate and (ii) constraint on aggregate rates. Both algorithms can be easily extended to design vector quantizers. 1 Introduction Source coding systems that are successively refinable or scalable in encoding rate have received growing attention recently. Such encoding systems have an embedded output bit stream; by selecting different sub-streams (stages of refinement) of the output, various levels of encoding rate and average distortion can be achieved. One immediate application of successive refinability (or, equivalently, rate-scalability) , which requires an embedded output bit stream, is in progressive transmission applications. Sometimes the utility of progressive transmission is readily apparent because it is central to an appl...
Keyphrases
entropy-constrained successively refinable scalar quantization average distortion output bit stream various level refinable scalar quantizers introduction source progressive transmission average rate embedded output bit successive refinability aggregate rate immediate application progressive transmission application different sub-streams vector quantizers
