Neural network method of intellectual processing of multispectral images

Main Article Content

Natalia Liubchenko
Andrii Podorozhniak
Viktor Bondarchuk

Abstract

The subject of the study in the article is the neural network method of object recognition on multispectral Earth remote sensing (ERS). The goal providing automatic recognition of objects illegal exploitation of natural resources in multispectral ERS images. The task is formulation of the method of intellectual processing of ERS data, which implements automatic recognition of objects of illegal use of natural resources on multispectral ERS images by using a convolutional neural network.. Analysis of the problems of methods and algorithms for processing multispectral aerospace images has shown that it is most promising to use flexible algorithms that adapt to changing conditions for observing search objects. One of the most promising technologies of the implementation of such algorithms is the use of neural networks. The selection of convolutional neural networks for solving the recognition problem is related to the ability of these networks, under the condition of correct training, to recognize objects under difficult observation conditions and when the observed object. Conclusions: the neural network method of intellectual processing of multispectral images is proposed. The algorithm for constructing this network is considered, the practical scope of the proposed method is chosen and the results of its program implementation are shown. The obtained results made it possible to conclude that the proposed algorithm is working and are the basis for further research into the development and implementation of processing algorithms for multispectral images in ERS systems.

Article Details

Section
Intelligent information systems
Author Biographies

Natalia Liubchenko, National Technical University "Kharkiv Polytechnic Institute", Kharkiv

Candidate of Technical Sciences, Associate Professor, Associate Professor of the Department of Informatics and Intellectual Property

Andrii Podorozhniak, National Technical University "Kharkiv Polytechnic Institute", Kharkiv

Candidate of Technical Sciences, Associate Professor, Associate Professor of the Department of Computer Science and Programming

Viktor Bondarchuk, National Technical University "Kharkiv Polytechnic Institute", Kharkiv

Student of the Department of Computer Science and Programming

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