Abstract
Markov models are used to quantify the spatial interactions of observed values at the nodes of a grid S and give a probability for any configuration x on S. In this chapter we review the classic presentation of Markov random fields with the assumption that the observed values at any site s ∈ S are discrete. This is true in most actual situations where sensors deliver digital images that are usually 8-bit encoded. This assumption simplifies the mathematics without limiting the applicability of these models.
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© 2003 Springer-Verlag New York, Inc.
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Chalmond, B. (2003). Fundamental Aspects. In: Modeling and Inverse Problems in Imaging Analysis. Applied Mathematical Sciences, vol 155. Springer, New York, NY. https://doi.org/10.1007/978-0-387-21662-1_5
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DOI: https://doi.org/10.1007/978-0-387-21662-1_5
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-3049-1
Online ISBN: 978-0-387-21662-1
eBook Packages: Springer Book Archive