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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 20, Iss. 6 — Mar. 12, 2012
  • pp: 6542–6554

Semi-Huber potential function for image segmentation

Osvaldo Gutiérrez, Ismael de la Rosa, Jesús Villa, Efrén González, and Nivia Escalante  »View Author Affiliations

Optics Express, Vol. 20, Issue 6, pp. 6542-6554 (2012)

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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.

© 2012 OSA

OCIS Codes
(100.0100) Image processing : Image processing
(100.2000) Image processing : Digital image processing

ToC Category:
Image Processing

Original Manuscript: September 23, 2011
Revised Manuscript: December 24, 2011
Manuscript Accepted: February 27, 2012
Published: March 6, 2012

Osvaldo Gutiérrez, Ismael de la Rosa, Jesús Villa, Efrén González, and Nivia Escalante, "Semi-Huber potential function for image segmentation," Opt. Express 20, 6542-6554 (2012)

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