Robinson, J.A. (2006) Adaptive prediction trees for image compression. IEEE Transactions on Image Processing, 15 ( 8). pp. 2131-2145. ISSN 1057-7149
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
Metadata
Item Type: | Article |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (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 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:6367 |