A Bayesian approach incorporating Rissanen complexity for learning Markov random field texture models

2002 ◽  
Author(s):  
K.R. Smith ◽  
M.I. Miller
Keyword(s):  
Random Field ◽  
Markov Random Field ◽  
Bayesian Approach ◽  
Markov Random

Utilization of Markov Random Field for Large Images: Multiframe Work and Bayesian Approach

2005 ◽  
Vol 277-279 ◽  
pp. 183-188
Author(s):  
Myung Hee Jung ◽  
Eui Jung Yun ◽  
Sy Woo Byun
Keyword(s):  
Random Field ◽  
Markov Random Field ◽  
Bayesian Approach ◽  
Computational Cost ◽  
Remotely Sensed Data ◽  
Global Features ◽  
Suggested Approach ◽  
Texture Modeling ◽  
Markov Random ◽  
Region Labeling

Markov Random Field (MRF) models have been successfully utilized in many digital image processing problems such as texture modeling and region labeling. Although MRF provides a well-defined statistical approach for the analysis of images, one disadvantage is the expensive computational cost for the processing and sampling of large images, since global features are assumed to be specified through local descriptions. In this study, a methodology is explored that reduces the computational burden and increases the speed of image analysis for large images, especially airborne and space-based remotely sensed data. The Bayesian approach is suggested as a reasonable alternative method in parameter estimation of MRF models; the utilization of a multiresolution framework is also investigated, which provides convenient and efficient structures for the transition between local and global features. The suggested approach is applied to the simulation of spatial pattern using MRF.

Markov random field aided Bayesian approach for image reconstruction in confocal microscopy

2007 ◽  
Vol 102 (4) ◽  
pp. 044701 ◽  
Author(s):  
Partha Pratim Mondal ◽  
Giuseppe Vicidomini ◽  
Alberto Diaspro
Keyword(s):  
Image Reconstruction ◽  
Confocal Microscopy ◽  
Random Field ◽  
Markov Random Field ◽  
Bayesian Approach ◽  
Markov Random

Fusion Moves for Markov Random Field Optimization

2010 ◽  
Vol 32 (8) ◽  
pp. 1392-1405 ◽  
Author(s):  
Victor Lempitsky ◽  
Carsten Rother ◽  
Stefan Roth ◽  
Andrew Blake
Keyword(s):  
Random Field ◽  
Markov Random Field ◽  
Markov Random
Sign in / Sign up

Export Citation Format

Share Document