REGION-BASED CLASSIFICATION OF ELECTRO-OPTICAL IMAGES WITH NEURAL NETWORKS AND FUZZY LOGIC

Authors

  • Iryna Petrosyuk
  • Yuri Zaichenko

DOI:

https://doi.org/10.47839/ijc.5.1.390

Keywords:

Fuzzy logic, hyperspectral remote sensing system, neural network

Abstract

This paper reports on a novel approach to the optical information processing for the hyperspectral remote sensing systems by means of developed unification algorithm of the two mathematical tools: the fuzzy logic and the neural network. New neuro-fuzzy classification algorithm for hyperspectral remote sensed images has been proposed. It is able to replace complicated empirical formulae, which require the knowledge of dependences of many input parameters that rapidly change during of range time and difficult for crisp determination.

References

Petrosyuk Irina, Neuro-Fuzzy Modeling in Underwater Imaging, Proc. 3th Conf. on Computing, Communications and Control Technologies CCCT '05 - July 24-27, 2005 - Austin, TX, USA.

V.M.Contarino, I.M.Petrosyuk. Neuro-Fuzzy Logic Application for Hyperspectral Remote Sensing. Proc.Conf on Remote Sensing of the Atmosphere, Ocean, Environment, and Space 2004, Honolulu, HW,USA.

Petrosyuk I.M., ZaichenkoY.P. Progressive Information Technologies Image Prosessing, Proc. 5rd International Conference on System Analysis and Information Technologies, 2005 - Kiev, Ukraine

Mark S. Nixon, Alberto S. Aguado, Feature Extraction and Image Processing (Oxford Press, UK, 2002)

Rumelhart B.E., Minton G.E., Williams R.J., 1986, Learning Representations by Back Propagating Error // Wature, V.323. pp.1016-1028.

ENVI Software (Version 4.0), September, 2003, Edition of Research System Inc.

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Published

2014-08-01

How to Cite

Petrosyuk, I., & Zaichenko, Y. (2014). REGION-BASED CLASSIFICATION OF ELECTRO-OPTICAL IMAGES WITH NEURAL NETWORKS AND FUZZY LOGIC. International Journal of Computing, 5(1), 117-123. https://doi.org/10.47839/ijc.5.1.390

Issue

2006, Volume 5, Issue 1

Section

Articles

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