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ICIP
2005
IEEE
15 years 11 months ago
A segmentation method using compound Markov random fields based on a general boundary model
Markov random field (MRF) theory has widely been applied to segmentation in noisy images. This paper proposes a new MRF method. First, it couples the original labeling MRF with a ...
Jue Wu, Albert C. S. Chung
CORR
2007
Springer
87views Education» more  CORR 2007»
14 years 9 months ago
Detection of Gauss-Markov Random Fields with Nearest-Neighbor Dependency
Abstract—The problem of hypothesis testing against independence for a Gauss–Markov random field (GMRF) is analyzed. Assuming an acyclic dependency graph, an expression for the...
Animashree Anandkumar, Lang Tong, Ananthram Swami
SIAMSC
2010
130views more  SIAMSC 2010»
14 years 4 months ago
Quasi-Monte Carlo Method for Infinitely Divisible Random Vectors via Series Representations
Infinitely divisible random vector without Gaussian component admits representations of shot noise series. Due to possible slow convergence of the series, they have not been inves...
Junichi Imai, Reiichiro Kawai
ECCV
2006
Springer
15 years 11 months ago
Random Walks, Constrained Multiple Hypothesis Testing and Image Enhancement
Image restoration is a keen problem of low level vision. In this paper, we propose a novel - assumption-free on the noise model - technique based on random walks for image enhancem...
Noura Azzabou, Nikos Paragios, Frederic Guichard
COMPGEOM
2009
ACM
15 years 4 months ago
Randomly removing g handles at once
It was shown in [11] that any orientable graph of genus g can be probabilistically embedded into a graph of genus g − 1 with constant distortion. Removing handles one by one giv...
Glencora Borradaile, James R. Lee, Anastasios Sidi...