DocumentCode :
3055862
Title :
A generalisation of renormalisation group methods for multiresolution image analysis
Author :
Nicholls, G.E. ; Petrou, M.
Author_Institution :
Dept. of Electron. & Electr. Eng., Surrey Univ., Guildford, UK
fYear :
1992
fDate :
30 Aug-3 Sep 1992
Firstpage :
567
Lastpage :
570
Abstract :
The application of multigrid methods to accelerating the minimisation of a nonconvex Gibbs potential requires that Gibbs parameters (GP´s) be chosen at each level of coarsening in such a way that the long-range conditional probabilities of the associated 2D Markov random field are unchanged by coarsening. Formulae specifying how GP´s transform from fine to coarse resolution exist for a restricted set of computationaly tractable cost functions and, while numerical routines solve the problem in principle, they are hopelessly slow for that class of spatially inhomogeneous GP´s (site parameters) which depend on the image data. The authors provide a general theorem which specifies how site parameters coarsen for deterministic linear block coarsening. The theorem can be used to accelerate the annealing of realistic image models
Keywords :
Markov processes; computational complexity; image processing; minimisation; simulated annealing; 2D Markov random field; deterministic linear block coarsening; minimisation; multigrid methods; multiresolution image analysis; nonconvex Gibbs potential; renormalisation group methods; site parameters; Annealing; Cost function; Ear; Image analysis; Image resolution; Lattices; Markov random fields; Minimization methods; Pixel; Spatial resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1992. Vol.I. Conference A: Computer Vision and Applications, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2910-X
Type :
conf
DOI :
10.1109/ICPR.1992.201625
Filename :
201625
Link To Document :
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