Abstract
We conclude this text with a sample of further typical applications. They once more illustrate the flexibility of the Bayesian framework. The first example concerns the analysis of motion. It shows how the ideas developed in the context of piecewise smoothing can be transfered to a problem of appearently different flavour. In single photon emission tomography — the second example — a similar approach is adopted. In contrast to former applications, shot noise is predominant here. The third example is different from the others. The basic elements are no longer pixel based like grey levels, labels or edge elements. They have an own structure and thereby a higher level of interpretation may be achieved. This is a hint along which lines middle or even high level image analysis might evolve. Part of the applications recently studied by leading researchers is presented in Chellapa and Jain (1993).
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© 1995 Springer-Verlag Berlin Heidelberg
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Winkler, G. (1995). Mixed Applications. In: Image Analysis, Random Fields and Dynamic Monte Carlo Methods. Applications of Mathematics, vol 27. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-97522-6_17
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DOI: https://doi.org/10.1007/978-3-642-97522-6_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-97524-0
Online ISBN: 978-3-642-97522-6
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