Abstract
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.
Highlights
Depending on the aircraft class and the list of tasks to be solved the aircraft technical vision system is represented by a different set of multispectral sensors
It may consist of color or monochrome television cameras, thermal imaging cameras, radar, lidar, ultrasonic sensors [1]
The tasks of fusion of a real television or thermal image (RI) with a virtual image (VI) synthesized from a digital terrain map is solved, the tasks of moving objects detection and tracking, etc. Another of the most important tasks solved as part of the onboard technical vision system is a reconstruction of a 3D model of the underlying surface in the Earth's plane using a stereo images pair sequence
Summary
Depending on the aircraft class and the list of tasks to be solved the aircraft technical vision system is represented by a different set of multispectral sensors. The tasks of fusion of a real television or thermal image (RI) with a virtual image (VI) synthesized from a digital terrain map is solved, the tasks of moving objects detection and tracking, etc. The primary processing unit solves the problems of image noise suppression, image enhancement, image fusion and edge detection Algorithms for this group of problems should have the lowest possible computational complexity and, at the same time, should provide a high-quality problem solution. Correlation algorithms are among the most efficient in terms of the geometric alignment accuracy of the real and virtual images and the accuracy of solving the inverse problem [10,11] These methods require the construction of the digital map views and for each view require the criterion function computation. The tracking mode is turned on, in which the navigation parameters values are estimated in a sliding mode as predicted values from the previous real values
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