Ways to improve objects recognition and classification in satellite images

Authors

  • Олена Михайлівна Гусак Private Higher Educational Institution "Bukovina University", Str. Darwin, 2-a, Chernivtsi, 58000, Ukraine

DOI:

https://doi.org/10.15587/2312-8372.2013.16232

Keywords:

satellite remote sensing, operator activity, multispectral satellite images operative monitoring

Abstract

The article analyzes modern technologies and methods to improve the efficiency of object recognition in satellite images, in particular the method of multispectral satellite high-resolution scans and their interpretation in a geographical information system (GIS).

Using multispectral images can improve the efficiency of objects recognition and classification. However, at a sufficiently high spectral resolution there is a problem related to the necessity of characteristics (spectral signatures) processing in high-dimensional spaces. The solution to this problem lies in the fact that first it is reasonable to reduce the space dimension and to perform recognition (classification) in the new space. Increasing of the separation ability resolves two interrelated objectives: improving of the visual quality and images reconstruction. Solution of the first problem is the method of fragmentation and zoning images. The solution of the second one is the deconvolution method.

The combination of area images processing and their reconstruction allow approaching solution of fire prediction problem and selection of distinguishing methods.

Author Biography

Олена Михайлівна Гусак, Private Higher Educational Institution "Bukovina University", Str. Darwin, 2-a, Chernivtsi, 58000

PhD student, lecturer in automated control systems

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Published

2013-07-24

How to Cite

Гусак, О. М. (2013). Ways to improve objects recognition and classification in satellite images. Technology Audit and Production Reserves, 4(1(12), 9–11. https://doi.org/10.15587/2312-8372.2013.16232

Issue

Vol. 4 No. 1(12) (2013): Technology audit and production reserves

Section

Technology audit

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Copyright (c) 2016 Олена Михайлівна Гусак

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