Development of computational method for matched filtration with analytical profile of the blurred digital image

Authors

DOI:

https://doi.org/10.15587/1729-4061.2022.265309

Keywords:

matched filter, transfer function, OLS evaluation, Gaussian, image processing

Abstract

A computational method for matched filtration with analytical profile of the blurred digital image of the investigated objects on digital frames has been developed. Such «blurred» objects can be the result of an involuntary shift of a fixed camera, an incorrect choice of the mode of guiding the telescope (diurnal or object tracking) or a failure of the diurnal tracking.

This computational method is based on the analytical selection of the typical form of the object’s image, as well as on the choice of special parameters for the transfer function of the matched filter for the blurred digital image, which makes it possible to evaluate the required parameters of the blurred digital image.

In addition, determining the number of Gaussians of the object’s image makes it possible to perform the most accurate assessment of the initial approximation of the parameters of their shape. Thus, matched filtration makes it possible to highlight the investigated objects with a blurred image of a typical shape against the background of substrate noise. Using the computational method of matched filtration makes it possible to improve the segmentation of images of reference objects on the frame and reduce the number of false detections.

The developed computational method for matched filtration with analytical profile of the blurred digital image of the investigated objects on the frames was tested in practice as part of the research of the CoLiTec project. It was implemented in the intraframe processing unit of the Lemur software for the operational automated detection of new and observation of known objects with a weak brightness. Owing to the Lemur software using and the proposed computational method introduced into it, more than 500,000 measurements of the various investigated objects were successfully processed and identified.

Author Biographies

Sergii Khlamov, SoftServe

PhD, Test Automation Lead

Vladimir Vlasenko, National Space Facilities Control and Test Center

PhD

Space Research and Communications Center

Vadym Savanevych, Kharkiv National University of Radio Electronics

Doctor of Technical Sciences, Professor

Department of Systems Engineering

Oleksandr Briukhovetskyi, National Space Facilities Control and Test Center

PhD

Western Center of Radiotechnical Surveillance

Tetiana Trunova, Kharkiv National University of Radio Electronics

Engineer

Department of Media Systems and Technologies

Victor Chelombitko, Kharkiv National University of Radio Electronics

PhD, Associate Professor

Department of Media Systems and Technologies

Iryna Tabakova, Kharkiv National University of Radio Electronics

PhD, Associate Professor

Department of Media Systems and Technologies

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Development of computational method for matched filtration with analytical profile of the blurred digital image

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Published

2022-10-30

How to Cite

Khlamov, S., Vlasenko, V., Savanevych, V., Briukhovetskyi, O., Trunova, T., Chelombitko, V., & Tabakova, I. (2022). Development of computational method for matched filtration with analytical profile of the blurred digital image . Eastern-European Journal of Enterprise Technologies, 5(4(119), 24–32. https://doi.org/10.15587/1729-4061.2022.265309

Issue

Vol. 5 No. 4(119) (2022): Mathematics and Cybernetics - applied aspects

Section

Mathematics and Cybernetics - applied aspects

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Copyright (c) 2022 Sergii Khlamov, Vladimir Vlasenko, Vadym Savanevych, Oleksandr Briukhovetskyi, Tetiana Trunova, Victor Chelombitko, Iryna Tabakova

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