Proceedings Article10.1109/ICASSP.1994.389323
Variable bit rate ADPCM via arithmetic coding
C.R. Watkins,S. Crisafulli,Robert R. Bitmead,Robert Orsi +3 more
- 19 Apr 1994
- pp 189-192
TL;DR: An ADPCM system, at an average bit rate of 16 kbps, produces a reconstructed speech signal that by informal listening tests has been judged to be of significantly higher quality than the LD-CELP 16Kbps speech coding standard.
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Abstract: Discusses the use of a variable bit rate ADPCM system for speech coding. The authors present an ADPCM system, using arithmetic coding and Kalman filtering techniques, that can code signals at very low bit rates, where standard fixed bit rate ADPCM systems fail. The proposed system, at an average bit rate of 16 kbps, produces a reconstructed speech signal that by informal listening tests has been judged to be of significantly higher quality than the LD-CELP 16 kbps speech coding standard. The authors believe that the output quality is comparable to that of LD-CELP at an average rate of around 12 kbps, and the quality at 8 kbps is very promising. Other advantages of the scheme are a reduction in complexity over the LD-CELP standard, and an increase in design flexibility. >
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References
Arithmetic coding for data compression
TL;DR: The state of the art in data compression is arithmetic coding, not the better-known Huffman method, which gives greater compression, is faster for adaptive models, and clearly separates the model from the channel encoding.
New methods for lossless image compression using arithmetic coding
Paul G. Howard,Jeffrey Scott Vitter +1 more
- 01 Aug 1991
TL;DR: This paper proposes a probabilistic model for lossless image compression that can be used to find and encode as much of the image structure of the data as possible, and then to encode efficiently the unstructured, noisy residual.
New methods for lossless image compression using arithmetic coding
TL;DR: This work presents two new methods (called MLP and PPPM) for lossless compression, both involving linear prediction, modeling prediction errors by estimating the variance of a Laplace distribution, and coding using arithmetic coding applied to precomputed distributions.
70
Parallel lossless image compression using Huffman and arithmetic coding
Paul G. Howard,Jeffrey Scott Vitter +1 more
- 24 Mar 1992
TL;DR: An algorithm based on the hierarchical multi-level progressive (MLP) method is presented, used either with Huffman coding or with a new variant of arithmetic coding called quasi-arithmetic coding.
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