Low complexity GMM-based block quantisation of images using the discrete cosine transform

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Title Low complexity GMM-based block quantisation of images using the discrete cosine transform
Author Paliwal, Kuldip Kumar; So, Stephen
Journal Name Signal Processing: Image Communication
Year Published 2005
Place of publication Amsterdam, The Netherlands
Publisher Elsevier
Abstract While block transform image coding has not been very popular lately in the presence of current state-of-the-art wavelet-based coders, the Gaussian mixture model (GMM)-based block quantiser, without the use of entropy coding, is still very competitive in the class of fixed rate transform coders. In this paper, a GMM-based block quantiser of low computational complexity is presented which is based on the discrete cosine transform (DCT). It is observed that the assumption of Gaussian mixture components in a GMM having Gauss-Markov properties is a reasonable one with the DCT approaching the optimality of the Karhunen-Lo\`eve transform (KLT) as a decorrelator. Performance gains of 6 to 7 dB are reported over the traditional single Gaussian block quantiser at 1 bit per pixel. The DCT possesses two advantages over the KLT: being fixed and source independent, which means it only needs to be applied once; and the availability of fast and efficient implementations. These advantages, together with bitrate scalability, result in a block quantiser that is considerably faster and less complex while the novelty of using a GMM to model the source probability density function is still preserved.
Peer Reviewed Yes
Published Yes
Publisher URI http://www.elsevier.com/wps/find/journaldescription.cws_home/505651/description#description
Alternative URI http://dx.doi.org/10.1016/j.image.2005.03.001
Copyright Statement Copyright 2005 Elsevier : Reproduced in accordance with the copyright policy of the publisher : This journal is available online - use hypertext links.
Volume 20
Page from 435
Page to 446
ISSN 0923-5965
Date Accessioned 2006-02-22
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Engineering and Information Technology
Subject PRE2009-Image Processing; PRE2009-Signal Processing
URI http://hdl.handle.net/10072/4281
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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