NDLI: Lossless Compression of Mapped Domain Linear Prediction Residual for ITU-T Recommendation G.711.0

Content Provider	IEEE Xplore Digital Library
Author	Harada, N. Kamamoto, Y. Moriya, T.
Copyright Year	2010
Abstract	ITU-T Rec. G.711 is widely used for the narrow band speech communication. ITU-T has just established a very low complexity and efficient lossless coding standard for G.711, called G.711.0 - Lossless compression of G.711 pulse code modulation. This paper introduces some coding technologies newly proposed and applied to the G.711.0 codec, such as Plus-Minus zero mapping for the mapped domain linear predictive coding and escaped-Huffman coding combined with adaptive recursive Rice coding for lossless compression of the prediction residual. Performance test results for those coding tools are shown in comparison with the results for the conventional technology. The performance is measured based on the figure of merit (FoM), which is a function of the trade-off between compression performance and computational complexity. The proposed tools improve the compression performance by 0.16% in total while keeping the computational complexity of encoder/decoder pair low (about 1.0 WMOPS in average and 1.667 WMOPS in the worst-case).
Starting Page	532
Ending Page	532
File Size	152869
Page Count	1
File Format	PDF
ISBN	9781424464258
ISSN	10680314
e-ISBN	9781424464265
DOI	10.1109/DCC.2010.69
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pulse modulation Codecs Performance evaluation Computational complexity Decoding Narrowband Internet telephony Payloads Pulse compression methods Modulation coding Mapped domain linear predictive coding Speech coding Standardization ITU-T Recommendation G.711.0 Lossless compression of G.711 payload Plus-Minus zero mapping Escaped-Huffman coding Adaptive recursive Rice coding
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

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