Por favor, use este identificador para citar o enlazar este ítem: http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1615
Título : A Comparative Study of Some Markov Random Fields and Different Criteria Optimization in Image Restoration
Autor : 31249
121858
Fecha de publicación : 14-mar-2012
Editorial : InTech
Resumen : The present chapter illustrates the use of some recent alternative methods to deal with digital image filtering and restoration. This collection of methods is inspired on the use of Markov Random Fields (MRF), which introduces prior knowledge of information that will allow, more efficiently, modeling the image acquisition process. The methods based on the MRF are analyzed and proposed into a Bayesian framework and their principal objective is to eliminate noise and some effects caused by excessive smoothness on the reconstruction process of images which are rich in contours or edges. In order to preserve object edges into the image, the use of certain convexity criteria into the MRF is proposed obtaining adequate weighting of cost functions in cases where discontinuities are remarked and, even better, for cases where such discontinuities are very smooth.
URI : http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1615
ISBN : 978- 953-51-0342-4
Otros identificadores : info:eu-repo/semantics/publishedVersion
Aparece en las colecciones: *Documentos Académicos*-- M. en Ciencias del Proc. de la Info.

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