Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-08T15:33:33.921Z Has data issue: false hasContentIssue false

Markov connected component fields

Published online by Cambridge University Press:  01 July 2016

Jesper M⊘ller
Affiliation:
University of Aalborg
Rasmus Waagepetersen
Affiliation:
University of Aarhus

Extract

A new class of Gibbsian models with potentials associated with the connected components or homogeneous parts of images is introduced. The relationship with Markov random fields and marked point processes is explored and spatial Markov properties are established. Further, extensions to infinite lattices are studied. Statistical inference problems including geostatistical applications and statistical image analysis are also discussed. Finally, simulation studies are presented which show that the models may be appropriate for a variety of interesting patterns.

Type
Stochastic Geometry and Statistical Applications
Copyright
Copyright © Applied Probability Trust 1996 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)