White Rose University Consortium logo
University of Leeds logo University of Sheffield logo York University logo

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

Full text not available from this repository.


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

Actions (repository staff only: login required)