DocumentCode
2477682
Title
Quantization as histogram segmentation: globally optimal scalar quantizer design in network systems
Author
Muresan, Dan ; Effros, Michelle
Author_Institution
Dept. of Electr. Eng., Stanford Univ., CA, USA
fYear
2002
fDate
2002
Firstpage
302
Lastpage
311
Abstract
We propose a polynomial-time algorithm for optimal scalar quantizer design on discrete-alphabet sources. Special cases of the proposed approach yield optimal design algorithms for fixed-rate and entropy-constrained scalar quantizers, multi-resolution scalar quantizers, multiple description scalar quantizers, and Wyner-Ziv scalar quantizers. The algorithm guarantees globally optimal solutions for fixed-rate and entropy-constrained scalar quantizers and constrained optima for the other coding scenarios. We derive the algorithm by demonstrating the connection between scalar quantization, histogram segmentation, and the shortest path problem in a certain directed acyclic graph.
Keywords
computational complexity; directed graphs; entropy codes; optimisation; quantisation (signal); statistical analysis; Wyner-Ziv scalar quantizers; codebook; coding; constrained optima; directed acyclic graph; discrete-alphabet sources; entropy-constrained scalar quantizers; fixed-rate scalar quantizers; globally optimal scalar quantizer; histogram segmentation; multi-resolution scalar quantizers; multiple description scalar quantizers; network systems; polynomial-time algorithm; quantization; shortest path problem; Algorithm design and analysis; Data compression; Decoding; Design optimization; Histograms; Intelligent networks; Partitioning algorithms; Polynomials; Quantization; Shortest path problem;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Compression Conference, 2002. Proceedings. DCC 2002
ISSN
1068-0314
Print_ISBN
0-7695-1477-4
Type
conf
DOI
10.1109/DCC.2002.999968
Filename
999968
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