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Occamian approach in the image restoration and other inverse problems
Author(s) -
Terebizh V. Yu.
Publication year - 1995
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.1850060409
Subject(s) - occam , inverse , inverse problem , image restoration , computer science , image (mathematics) , algorithm , bayesian probability , fisher information , object (grammar) , mathematics , maximum likelihood , mathematical optimization , artificial intelligence , image processing , statistics , machine learning , mathematical analysis , geometry , programming language
Abstract A non‐Bayesian approach to inverse problems is discussed in terms of the image restoration problem. The approach is based on the extended notion of the feasible estimate and on the Occam's principle of choosing the simplest object, consistent with the data. The Occamian estimation is performed by transforming the inverse or maximum likelihood estimate to its principal components, which are induced by Fisher's information matrix.