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Image compression using linear prediction operator of wavelet coefficients

Authors:

S. Selvarajan ,

Vavuniya Campus of the University of Jaffna, LK
About S.
Department of Physical Science, Faculty of Applied Science, Vavuniya Campus of the University of Jaffna, Park Road, Vavuniya
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N. D. Kodikara,

University of Colombo School of Computing, LK
About N. D.
Department of Information Systems Engineering, University of Colombo School of Computing, 35, Reid Avenue, Colombo 7.
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G. D. S. P. Wimalaratne

University of Colombo School of Computing, LK
About G. D. S. P.
Department of Communication and Media Technology, University of Colombo School of Computing, 35, Reid Avenue, Colombo 7
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Abstract

In this paper, we propose a new prediction operator called the linear prediction operator. The linear prediction operator is based on the explicit model of statistical relationship of the high-frequency coefficients between the different frequency sub-bands and the scaled similarity of the high-frequency coefficients with respect to their orientations. This scaled similarity is exploited to approximate the functions in different resolutions to achieve high compression ratio.

Keywords: Fractal coding, haar transform, multi resolution analysis, nonlinear approximation, zero-tree wavelet

doi :10.4038/jnsfsr.v37i3.1210

J.Natn.Sci.Foundation Sri Lanka 2009 37 (3): 167-174

 

 

 

How to Cite: Selvarajan, S., Kodikara, N.D. and Wimalaratne, G.D.S.P., 2009. Image compression using linear prediction operator of wavelet coefficients. Journal of the National Science Foundation of Sri Lanka, 37(3), pp.167–174. DOI: http://doi.org/10.4038/jnsfsr.v37i3.1210
Published on 26 Sep 2009.
Peer Reviewed

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