Cluster approximations for statistical image processing

Chi-hsin Wu; Peter C. Doerschuk

doi:10.1117/12.162051

29 October 1993 Cluster approximations for statistical image processing

Chi-hsin Wu, Peter C. Doerschuk

Proceedings Volume 2032, Neural and Stochastic Methods in Image and Signal Processing II; (1993) https://doi.org/10.1117/12.162051
Event: SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, 1993, San Diego, CA, United States

Abstract

A disadvantage of using discrete-state Markov random field models of images is that optimal estimators for reconstruction problems require excessive and typically random amounts of computation. In one approach the key task is the computation of the conditional mean of the field given the data or equivalently the unconditional mean of the a posteriori field. In this paper we describe a hierarchy of deterministic parallelizable methods for such computations.

Citation Download Citation

Chi-hsin Wu and Peter C. Doerschuk "Cluster approximations for statistical image processing", Proc. SPIE 2032, Neural and Stochastic Methods in Image and Signal Processing II, (29 October 1993); https://doi.org/10.1117/12.162051

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