Adaptive Boolean predictive modeling with application to lossless image coding

Ioan Tabus; Jaakko T. Astola

doi:10.1117/12.279644

14 October 1997 Adaptive Boolean predictive modeling with application to lossless image coding

Ioan Tabus, Jaakko T. Astola

Proceedings Volume 3167, Statistical and Stochastic Methods in Image Processing II; (1997) https://doi.org/10.1117/12.279644
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

This paper develops new algorithms belonging to the class of context modeling methods, with direct application to lossless coding of gray level images. The prediction stage and the context modeling stage are performed using nonlinear techniques rooted in the field of order statistics nonlinear filtering, which proved competitive in image restoration applications. The new nonlinear predictors introduced here can be easily rephrased as adaptive nonlinear filtering tools, useful in image restoration applications. We propose a new variant of the Context algorithm, where the prediction, modeling of errors and coding are realized using a Finite State Machine modeler, (which reduces the complexity of tree modelers, by lumping together similar nodes). The coding performance of the new Context algorithm is better than that of the best available algorithms, as illustrated in the experimental section.

Citation Download Citation

Ioan Tabus and Jaakko T. Astola "Adaptive Boolean predictive modeling with application to lossless image coding", Proc. SPIE 3167, Statistical and Stochastic Methods in Image Processing II, (14 October 1997); https://doi.org/10.1117/12.279644

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