Markov random fields for catadioptric image processing

Authors:
Cédric Demonceaux;Pascal Vasseur
Affiliations:
CREA-EA 3299, University of Picardie Jules Verne, 7 Rue du Moulin Neuf, 80000 Amiens, France;CREA-EA 3299, University of Picardie Jules Verne, 7 Rue du Moulin Neuf, 80000 Amiens, France
Venue:
Pattern Recognition Letters
Year:
2006

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Abstract

Images obtained with catadioptric sensors contain significant deformations which prevent the direct use of classical image treatments. Thus, Markov random fields (MRF) whose usefulness is now obvious for projective image processing, cannot be used directly on catadioptric images because of the inadequacy of the neighborhood. In this paper, we propose to define a new neighborhood for MRF by using the equivalence theorem developed for central catadioptric sensors. We show the importance of this adaptation for segmentation, image restoration and motion detection.