Multi-component image segmentation in homogeneous regions based on description length minimization: Application to speckle, Poisson and Bernoulli noise

Authors:
Frédéric Galland;Nicolas Bertaux;Philippe Réfrégier
Affiliations:
Physics and Image Processing Group, Fresnel Institute, UMR CNRS 6133, EGIM, Domaine Universitaire de St Jérôme, 13397 Marseille, Cedex 20, France;Physics and Image Processing Group, Fresnel Institute, UMR CNRS 6133, EGIM, Domaine Universitaire de St Jérôme, 13397 Marseille, Cedex 20, France;Physics and Image Processing Group, Fresnel Institute, UMR CNRS 6133, EGIM, Domaine Universitaire de St Jérôme, 13397 Marseille, Cedex 20, France
Venue:
Pattern Recognition
Year:
2005

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Abstract

In this article, a minimum description length (MDL) criterion adapted to independent multi-component image segmentation into homogeneous regions is proposed. This approach, based on a deformable polygonal grid, allows us to segment noisy multi-component images perturbed with spatially independent speckle, Poisson or Bernoulli noise. The advantages of using such a multi-component approach rather than a mono-component one is demonstrated on synthetic and real images. This segmentation method is also applicable to multi-component images whose components do not follow the same noise statistics or have not been previously registered.