DocumentCode :
390774
Title :
Scalable predictive coding as the Wyner-Ziv problem
Author :
Sehgal, Anshul ; Jagmohan, Ashish ; Ahuja, Narendra
Author_Institution :
Illinois Univ., Chicago, IL, USA
Volume :
1
fYear :
2002
fDate :
25-28 Nov. 2002
Firstpage :
101
Abstract :
An alternative to scalable predictive coding of first order Gauss-Markov processes is proposed in this paper. It is shown that conventional scalable predictive coding is inherently suboptimal. An alternative to scalable predictive coding, which achieves the rate-distortion performance of predictive coding for first-order Gauss-Markov processes is then proposed. The proposed approach is posed as a variant of the well-known Wyner-Ziv (1976) problem. By using coset codes with nested lattices, the present paper proves that the proposed approach achieves the predictive coding bound asymptotically at all scales while simultaneously providing the functionality of scalable coding.
Keywords :
Gaussian processes; Markov processes; decoding; encoding; prediction theory; rate distortion theory; Wyner-Ziv problem; continuous random variable; correlated side information; coset codes; decoding algorithm; first order Gauss-Markov process; nested lattices; predictive coding bound; rate-distortion performance; scalable predictive coding; suboptimal coding; Decoding; Gaussian processes; Image coding; Image reconstruction; Internet; Predictive coding; Rate-distortion; Redundancy; Streaming media; Video compression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication Systems, 2002. ICCS 2002. The 8th International Conference on
Print_ISBN :
0-7803-7510-6
Type :
conf
DOI :
10.1109/ICCS.2002.1182446
Filename :
1182446
Link To Document :
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