2013 | OriginalPaper | Buchkapitel
Expert Regularizers for Task Specific Processing
verfasst von : Guy Gilboa
Erschienen in: Scale Space and Variational Methods in Computer Vision
Verlag: Springer Berlin Heidelberg
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This study is concerned with constructing expert regularizers for specific tasks. We discuss the general problem of what is desired from a regularizer, when one knows the type of images to be processed. The aim is to improve the processing quality and to reduce artifacts created by standard, general-purpose, regularizers, such as total-variation or nonlocal functionals.
Fundamental requirements for the theoretic expert regularizer are formulated. A simplistic regularizer is then presented, which approximates in some sense the ideal requirements.