BAYESIAN IMAGE RESTORATION VIA VARYING NEIGHBORHOOD STRUCTURE

Abstract

A modified method for Bayesian image restoration using varying neighborhood structure is proposed. The method reduces computational burden for yielding a restored image due to the dynamical change of structural forms of neighborhood, which should be iteratively and adaptively composed through the process of the restoration calculation. Although, in practice, the results of restoration generally depend on given data, our simulation results show that the method is effective for some given gray-scale images with moderate additive Gaussian noise.

Journal

Journal of the Japanese Society of Computational Statistics   [List of Volumes]

Journal of the Japanese Society of Computational Statistics 14(1), 31-47, 2001-12  [Table of Contents]

Japanese Society of Computational Statistics

References:  13

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Codes

  • NII Article ID (NAID) :
    110001235639
  • NII NACSIS-CAT ID (NCID) :
    AA10823693
  • Text Lang :
    ENG
  • Article Type :
    ART
  • ISSN :
    09152350
  • Databases :
    CJP  NII-ELS 

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