Annals of the Institute of Statistical Mathematics

, Volume 43, Issue 1, pp 1–20

Bayesian image restoration, with two applications in spatial statistics

Authors

  • Julian Besag
    • Department of Statistics GN-22University of Washington
  • Jeremy York
    • Department of Statistics GN-22University of Washington
  • Annie Mollié
    • Institut Gustave RoussyINSERM U287
Bayesian Image Analysis (with Discussion)

DOI: 10.1007/BF00116466

Cite this article as:
Besag, J., York, J. & Mollié, A. Ann Inst Stat Math (1991) 43: 1. doi:10.1007/BF00116466

Abstract

There has been much recent interest in Bayesian image analysis, including such topics as removal of blur and noise, detection of object boundaries, classification of textures, and reconstruction of two- or three-dimensional scenes from noisy lower-dimensional views. Perhaps the most straightforward task is that of image restoration, though it is often suggested that this is an area of relatively minor practical importance. The present paper argues the contrary, since many problems in the analysis of spatial data can be interpreted as problems of image restoration. Furthermore, the amounts of data involved allow routine use of computer intensive methods, such as the Gibbs sampler, that are not yet practicable for conventional images. Two examples are given, one in archeology, the other in epidemiology. These are preceded by a partial review of pixel-based Bayesian image analysis.

Key words and phrases

Bayesian restorationimage analysisspatial statisticsGibbs samplerarcheologyepidemiology
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© Kluwer Academic Publisher 1990