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SSIAI
2000
IEEE
13 years 9 months ago
Pairwise Markov Random Fields and its Application in Textured Images Segmentation
The use of random fields, which allows one to take into account the spatial interaction among random variables in complex systems, is a frequent tool in numerous problems of stati...
Wojciech Pieczynski, Abdel-Nasser Tebbache
ICASSP
2011
IEEE
12 years 8 months ago
A new stochastic image model based on Markov random fields and its application to texture modeling
Stochastic image modeling based on conventional Markov random fields is extensively discussed in the literature. A new stochastic image model based on Markov random fields is intr...
Siamak Yousefi, Nasser D. Kehtarnavaz
ICIP
2007
IEEE
14 years 6 months ago
Automatic Parametrisation for an Image Completion Method Based on Markov Random Fields
Recently, a new exemplar-based method for image completion, texture synthesis and image inpainting was proposed which uses a discrete global optimization strategy based on Markov ...
Huy Tho Ho, Roland Göcke
MICCAI
2005
Springer
14 years 5 months ago
Cross Entropy: A New Solver for Markov Random Field Modeling and Applications to Medical Image Segmentation
This paper introduces a novel solver, namely cross entropy (CE), into the MRF theory for medical image segmentation. The solver, which is based on the theory of rare event simulati...
Jue Wu, Albert C. S. Chung
ECCV
2008
Springer
14 years 6 months ago
Sparse Long-Range Random Field and Its Application to Image Denoising
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...
Yunpeng Li, Daniel P. Huttenlocher