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Design of forward adaptive hybrid quantiser with Golomb–Rice code for compression of Gaussian source
Author(s) -
Perić Zoran H.,
Nikolić Jelena R.,
Mosić Aleksandar V.
Publication year - 2014
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2012.0791
Subject(s) - golomb coding , mathematics , algorithm , speech recognition , computer science , artificial intelligence , image compression , image (mathematics) , image processing
This study proposes a novel model of hybrid quantiser composed of a uniform scalar quantiser and a non‐uniform optimal companding scalar quantiser, both designed for a Gaussian source. We examine whether by appropriately designing a novel forward adaptive hybrid quantiser with Golomb–Rice code, one can achieve more sophisticated compression and a higher signal to quantisation noise ratio compared with the uniform quantiser with Golomb–Rice code. We observe which value of the bit rate should be chosen to provide high‐quality quantisation. It is shown that the authors compression model can satisfy G.712 recommendation for high‐quality quantisation achieving the compression of 1.68 bit/sample over the G.711 quantiser. In addition, for the average bit rate of 6.32 bit/sample their hybrid quantiser outperforms the uniform quantiser for 1.32 dB. The presented performances of the forward adaptive hybrid quantiser indicate that it should be of theoretical and practical significance in quantisation of the Gaussian source signals.

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