July 2010
Intermediate to advanced
1384 pages
74h 23m
English
P. Fieguth, University of Waterloo, Ontario
J. Zhang, University of Wisconsin, Milwaukee
2.1 Markov Random Fields
2.2 Gauss-Markov Random Fields
2.3 Gibbs Random Fields
3.1 Discrete-State Models
3.2 Continuous-State Models
3.3 Examples
4 A Nonlinear/Non-Gaussian Model: the Gaussian Mixture.
4.1 The Gaussian Mixture Model
4.2 Some Applications
Random fluctuations in intensity, color, texture, object boundary or shape can be seen in most real-world images, as illustrated in Fig. 1. The causes for these fluctuations are diverse and complex, often due to factors such as non-uniform lighting, ...
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