Robinson, J.A. (2006) Adaptive prediction trees for image compression. IEEE Transactions on Image Processing, 15 ( 8). pp. 2131-2145. ISSN 1057-7149Full 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
|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|
|Publisher:||Institute of Electrical and Electronics Engineers (IEEE)|