O'Reilly logo

Digital Video Processing, Second Edition by A. Murat Tekalp

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Appendix C. Markov and Gibbs Random Fields

Markov random fields specified in terms of Gibbs distributions have become popular as a priori models in Bayesian formulations for image processing applications such texture modeling and generation [Cro 83, Che 93], image segmentation and restoration [Gem 84, Der 87, Pap 92], and motion estimation [Dub 93]. This appendix provides the definitions of a Markov random field and the Gibbs distribution, and then describe their relationship by means of the Hammersley-Clifford theorem. The specification of MRFs in terms of Gibbs distributions has led to the terminology “Gibbs random field” (GRF). We also discuss how to obtain the local (Markov) conditional pdfs from the Gibbs distribution, which is a joint pdf. ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required