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Adaptive prediction trees for image compression

Robinson, J.A. (2006) Adaptive prediction trees for image compression. IEEE Transactions on Image Processing, 15 ( 8). pp. 2131-2145. ISSN 1057-7149

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Abstract

This paper presents a complete general-purpose method for still-image compression called adaptive prediction trees. Efficient lossy and lossless compression of photographs, graphics, textual, and mixed images is achieved by ordering the data in a multicomponent binary pyramid, applying an empirically optimized nonlinear predictor, exploiting structural redundancies between color components, then coding with hex-trees and adaptive runlength/Huffman coders. Color palettization and order statistics prefiltering are applied adaptively as appropriate. Over a diverse image test set, the method outperforms standard lossless and lossy alternatives. The competing lossy alternatives use block transforms and wavelets in well-studied configurations. A major result of this paper is that predictive coding is a viable and sometimes preferable alternative to these methods

Item Type: Article
Institution: The University of York
Academic Units: The University of York > Electronics (York)
Depositing User: York RAE Import
Date Deposited: 15 May 2009 13:38
Last Modified: 15 May 2009 13:38
Published Version: http://dx.doi.org/10.1109/TIP.2006.875196
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Identification Number: 10.1109/TIP.2006.875196
URI: http://eprints.whiterose.ac.uk/id/eprint/6367

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