| Issue |
E3S Web Conf.
Volume 224, 2020
Topical Problems of Agriculture, Civil and Environmental Engineering (TPACEE 2020)
|
|
|---|---|---|
| Article Number | 02025 | |
| Number of page(s) | 12 | |
| Section | Information Technologies for Environmental Sustainability | |
| DOI | https://doi.org/10.1051/e3sconf/202022402025 | |
| Published online | 23 December 2020 | |
Mathematical modelling of an airborne technical vision system development
Ryazan state radio engineering university named after V.F. Utkin, 59/1, Gagarina str, Ryazan, 390005, Russia
* Corresponding author: novikovanatoly@yandex.ru
An airborne technical vision system of a modern aircraft is, on the one hand, a complex of multispectral sensors and, on the other, airborne computer equipment. The onboard computer solves a wide range of complex digital image processing tasks. The strict requirements are imposed on the computer mathematical software on the image processing time and on the quality of the result displayed on the pilot screen. The software development for such a complex system involves mathematical modelling and use modern information technologies in process of computational algorithms development for task solving. The proposed work discusses ways of solving subtasks of one of the most important subsystems of the airborne complex - the image fusion subsystem and solving the inverse navigation problem. The subsystem is represented by two blocks of tasks: tasks of primary image processing and high-level tasks. The primary processing unit solves the problems of image noise suppression, image enhancement, image fusion and edge detection. In the high-level block of tasks, the tasks of key points detection on real and virtual images, the tasks of a geometric transformation estimation of one image to the plane of another, and the task of a 3D model construction of the underlying surface are solved. The paper presents the results of mathematical modelling in the process of algorithms development for above problems solving. The new results of mathematical modelling of the noise estimation problem are presented in detail. The description of methods and results of other problems solving is less detailed due to article limit but provided with links to the corresponding publications of the authors.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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