Methods of Estimation and Processing of Aerospace Information in Image Contouring Problem

Authors

  • Andrey A. Galyaev V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russia
  • Alexander V. Dobrovidov V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russia
  • Pavel V. Lysenko V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russia
  • Leonid M. Berlin V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russia
  • Maria A. Kolygo V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russia

DOI:

https://doi.org/10.25728/assa.2024.24.1.1565

Keywords:

Earth’s surface monitoring, image segmentation and contouring problem, aerospace information processing

Abstract

The article proposes approaches to the solution of the segmentation problem of real satellite images based on random Markov vector fields and new statistical textural characteristics for gray-level co-occurrence matrix. The authors introduce a novel image textural characteristic called statistical complexity that successfully distinguishes deterministic structures on naturally or artificially noised images. Software modules have been developed and satellite image examples are processed in order to determine the contours of the land structures and the presence of static and dynamic objects on the ocean surface. A comparison of two segmentation methods on real images has been made, which showed the prospects of their use in automatic image processing.

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Published

2024-04-02

How to Cite

Galyaev, A. A., Dobrovidov, A. V., Lysenko, P. V., Berlin, L. M., & Kolygo, M. A. (2024). Methods of Estimation and Processing of Aerospace Information in Image Contouring Problem. Advances in Systems Science and Applications, 24(1), 20–28. https://doi.org/10.25728/assa.2024.24.1.1565