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IMAGE MODELING AND RESTORATION THROUGH CONTAGION URN SCHEMES
 

Summary: IMAGE MODELING AND RESTORATION
THROUGH CONTAGION URN SCHEMES
Fady Alajaji y and Philippe Burlina z
y Department of Mathematics and Statistics, Queen's University, Kingston, ON K7L 3N6, Canada.
z Center for Automation Research, University of Maryland, College Park, MD 20742, USA.
ABSTRACT
We introduce a novel class of nonlinear stochastic filters
based on contagion urn schemes. These filters which
rely on biologically inspired sampling processes, offer
good restoration results on heavily corrupted binary
images.
1. INTRODUCTION
We present a new approach to binary image filtering
using contagion urn schemes. Techniques modeling im­
ages as Markov random fields (MRF) have been exten­
sively investigated in the past [1, 2]. MRF's appro­
priately represent spatial dependencies and the MRF­
Gibbs equivalence allows for the computation of the
maximum a posteriori (MAP) estimate of the original
image [1]. This approach suffers nevertheless from var­

  

Source: Alajaji, Fady - Department of Mathematics and Statistics, Queen's University (Kingston)

 

Collections: Engineering