DocumentCode
1007766
Title
A structured fixed-rate vector quantizer derived from a variable-length scalar quantizer. II. Vector sources
Author
Loroia, Rajiv ; Farvardin, Nariman
Author_Institution
AT&T Bell Lab., Murray Hill, NJ, USA
Volume
39
Issue
3
fYear
1993
fDate
5/1/1993 12:00:00 AM
Firstpage
868
Lastpage
876
Abstract
For Pt.I see ibid., vol.39, no.3, p.851-67 (1993). The fixed-rate scalar-vector quantizer (SVQ) for quantizing stationary memoryless sources is extended to a specific type of vector source in which each component is a stationary memoryless scalar subsource independent of the other components. Algorithms for the design and implementation of the original SVQ are modified to apply to this case. The resulting SVQ, referred to as the extended SVQ (ESVQ), is then used to quantize stationary sources with memory (with known autocorrelation function). Numerical results are presented for the quantization of first-order Gauss-Markov sources using this scheme. It is shown that the ESVQ-based scheme performs very close to entropy-coded transform quantization while maintaining a fixed-rate output and outperforms the fixed-rate scheme that uses scalar Lloyd-Max quantization of the transform coefficients. It is also shown that this scheme performs better than implementable vector quantizers, especially at high rates
Keywords
coding errors; vector quantisation; extended SVQ; first-order Gauss-Markov sources; scalar-vector quantizer; stationary memoryless scalar subsource; structured fixed-rate vector quantizer; variable-length scalar quantizer; vector source; Algorithm design and analysis; Autocorrelation; Bridges; Decorrelation; Gaussian processes; Helium; Karhunen-Loeve transforms; Polynomials; Quantization; Vectors;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.256494
Filename
256494
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