Image processing algorithms based on finite-state Gibbs models

被引：0
|
作者：
Vasyukov, Vasily N. [1 ]
机构：
[1] Novosibirsk State Tech Univ, Novosibirsk 630092, Russia
来源：
IFOST 2006: 1st International Forum on Strategic Technology, Proceedings: E-VEHICLE TECHNOLOGY | 2006年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Gibbs (Markov) random fields are used as stochastic picture models in image processing because of their conceptual simplicity and due to the fact that Gibbs models are fit to synthesize algorithms based on Bayes approach. In this paper, we are concerned with Gibbs fields taking on values from finite sets. This restriction allows to overcome difficulties in estimating Gibbs distribution parameters and to synthesize some useful algorithms of image processing.
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收藏
页码：287 / 288
页数：2
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