Multiscale and Critical Markov Random Fields
Author : Raja Ghozi
Publisher :
Page : 306 pages
File Size : 21,68 MB
Release : 1998
Category :
ISBN :
Author : Raja Ghozi
Publisher :
Page : 306 pages
File Size : 21,68 MB
Release : 1998
Category :
ISBN :
Author :
Publisher :
Page : 8 pages
File Size : 29,45 MB
Release : 1992
Category :
ISBN :
Author : F. Heitz
Publisher :
Page : 39 pages
File Size : 45,38 MB
Release : 1992
Category :
ISBN :
Author : M. R. Luettgen
Publisher :
Page : 58 pages
File Size : 26,93 MB
Release : 1992
Category : Markov processes
ISBN :
Author : Fabrice Heitz
Publisher :
Page : 40 pages
File Size : 41,78 MB
Release : 1992
Category :
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Author : Uğur Sıvakçı
Publisher :
Page : pages
File Size : 36,89 MB
Release : 1998
Category :
ISBN :
Author : Y.A. Rozanov
Publisher : Springer Science & Business Media
Page : 207 pages
File Size : 25,47 MB
Release : 2012-12-06
Category : Mathematics
ISBN : 1461381908
In this book we study Markov random functions of several variables. What is traditionally meant by the Markov property for a random process (a random function of one time variable) is connected to the concept of the phase state of the process and refers to the independence of the behavior of the process in the future from its behavior in the past, given knowledge of its state at the present moment. Extension to a generalized random process immediately raises nontrivial questions about the definition of a suitable" phase state," so that given the state, future behavior does not depend on past behavior. Attempts to translate the Markov property to random functions of multi-dimensional "time," where the role of "past" and "future" are taken by arbitrary complementary regions in an appro priate multi-dimensional time domain have, until comparatively recently, been carried out only in the framework of isolated examples. How the Markov property should be formulated for generalized random functions of several variables is the principal question in this book. We think that it has been substantially answered by recent results establishing the Markov property for a whole collection of different classes of random functions. These results are interesting for their applications as well as for the theory. In establishing them, we found it useful to introduce a general probability model which we have called a random field. In this book we investigate random fields on continuous time domains. Contents CHAPTER 1 General Facts About Probability Distributions §1.
Author : Fabrice Heitz
Publisher :
Page : 40 pages
File Size : 24,28 MB
Release : 1992
Category : Computer vision
ISBN :
The efficiency of the approach is demonstrated on several relevant problems in image sequence analysis : motion detection, optical flow measurement and motion-based segmentation. Results are presented on real world sequences including several moving objects and camera motion."
Author : Fabrice Heitz
Publisher :
Page : 40 pages
File Size : 44,48 MB
Release : 1992
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Author : Mark Robert Luettgen
Publisher :
Page : 58 pages
File Size : 14,33 MB
Release : 1992
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ISBN :