Adaptive prediction trees for image compression.

John A Robinson

doi:10.1109/tip.2006.875196

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PubMed · 16900671

Adaptive prediction trees for image compression.

John A Robinson

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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.

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Algorithms Computer Graphics Data Compression Image Enhancement Image Interpretation, Computer-Assisted Numerical Analysis, Computer-Assisted Pattern Recognition, Automated Signal Processing, Computer-Assisted Journal Article

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John A Robinson. 2006. Adaptive prediction trees for image compression.. https://doi.org/10.1109/tip.2006.875196

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