Please use this identifier to cite or link to this item: http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1866
Title: Bayesian Filtering and Some Markovian Random Fields for Image Restoration
Authors: De la Rosa Vargas, José Ismael
Villa Hernández, José de Jesús
González, Efrén
Araiza Esquivel, María Auxiliadora
Gutiérrez, Osvaldo
Escobar, María de la Luz
Fleury, Gilles
Issue Date: Nov-2011
Publisher: ROPEC
IEEE
Abstract: The present work introduces an alternative method to deal with digital image restoration into a Bayesian framework, particularly, the use of a new half-quadratic function is proposed. The Bayesian methodology is based on the prior knowledge of some information that allows an e±cient modelling of the image acquisition process. The edge preservation of objects into the image while smoothing noise is necessary in an adequate model. Thus, we use a convexity criteria given by a semi-Huber function to obtain adequate weighting of the cost functions (half-quadratic) to be minimized. A comparison between the new introduced scheme and other three existent schemes, for the cases of noise ¯ltering and image deblurring, is presented. Results showed a satisfactory performance and the effectiveness of the proposed estimator.
URI: http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1866
https://doi.org/10.48779/ebxw-8s51
ISBN: 978-607-95476-3-9
Other Identifiers: info:eu-repo/semantics/publishedVersion
Appears in Collections:*Documentos Académicos*-- M. en Ciencias del Proc. de la Info.

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