Modeling alternatives for fuzzy Markov chain-based classification of multitemporal remote sensing data
Modeling alternatives for fuzzy Markov chain-based classification of multitemporal remote sensing data
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DOI：
10.1016/j.patrec.2010.09.024
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发表时间：
2011-05-01
影响因子：
5.1
通讯作者：
Feijo, Bruno
中科院分区：
文献类型：
--
作者：
Feitosa, Raul Queiroz;Ostwald Pedro da Costa, Gilson Alexandre;Feijo, Bruno
在这项工作中，我们研究了基于模糊马尔可夫链的遥感数据多时相级联分类建模方案的应用。从理论角度出发，正式提出了基于模糊马尔可夫链模型的备选设计方案。从实用的角度出发，对实验结果进行了讨论和分析，进一步了解了基于模糊马尔可夫链的多时相遥感数据分类的优点和优势。我们认为基于模糊马尔可夫链的多时间分类模型的关键组成部分是t-范数和s-范数算子，以及模糊聚合函数。本文的主要目的是研究一个特定的设计是如何影响分类性能的。此外，本文旨在根据所选择的设计方案评估单时间分类器的准确性对多时间分类结果质量的影响。总之，本文为图像分析系统的开发人员和基于模糊马尔可夫链的分类方法的设计者提供了设计指南。(C) 2010 Elsevier B.V.版权所有
In this work, we investigate the application of modeling alternatives regarding fuzzy Markov chain-based, multitemporal, cascade classification of remote sensing data. From a theoretical viewpoint, alternative designs for the fuzzy Markov chain-based model are formally presented. From a pragmatic perspective, experimental results are discussed and analyzed, providing a deeper understanding of the virtues and odds of multitemporal remote sensing data classification based on fuzzy Markov chains. We claim that the key components of the fuzzy Markov chain-based, multitemporal classification model with respect to its alternative designs are the t-norm and s-norm operators, and the fuzzy aggregation function. The main objective of this paper is to investigate how a particular design may affect the classification performance. In addition, this paper aims at assessing the impact of the monotemporal classifiers' accuracies on the quality of the multitemporal classification outcome, according to the selected design alternatives. In conclusion, this paper presents design guidelines for both the developer of image analysis systems and the designer of classification methods based on fuzzy Markov chains. (C) 2010 Elsevier B.V. All rights reserved.