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Semi-Huber potential function for image segmentation
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DOI：10.1364/OE.20.006542.png)
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Abstract
En 中文
In this work, a novel model of Markov Random Field (MRF) is introduced. Such a model is based on a proposed Semi-Huber potential function and it is applied successfully to image segmentation in presence of noise. The main difference with respect to other half-quadratic models that have been taken as a reference is, that the number of parameters to be tuned in the proposed model is smaller and simpler. The idea is then, to choose adequate parameter values heuristically for a good segmentation of the image. In that sense, some experimental results show that the proposed model allows an easier parameter adjustment with reasonable computation times. (C) 2012 Optical Society of America
Keywords:
FIELD MODELS
MARKOV
REGULARIZATION
RESTORATION
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