Журнал Российского общества по неразрушающему контролю и технической диагностике
The journal of the Russian society for non-destructive testing and technical diagnostic
 
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22 | 12 | 2024
2022, 04 April

DOI: 10.14489/td.2022.04.pp.020-031

Makhov V. E., Shirobokov V. V., Emelyanov A. V., Potapov A. I.
INVESTIGATION OF ALGORITHMS OF DETECTING OF THE CHARACTERISTICS OF REMOTE OBJECTS IN OPTOELECTRONIC SYSTEMS BY THE METHOD OF WAVELET TRANSFORMATION
(pp. 20-31)

Abstract. The issues of the accuracy of measuring the coordinates and size of objects observed by an optical system by the methods of single and double continuous wavelet transform in their image are considered. It is shown that the use of the second continuous wavelet transform to the curves of the coefficients of the first transform leads to an increase in the extrema of the scalegram and the smoothness of the curves of the coefficients, providing more than two times higher coordinate sensitivity of determining the position and orientation of objects. The use of different types of wavelets in each continuous wavelet transform of signals gives many options for the curves of the coefficients of the continuous wavelet transform and can be used for additional filtering of noise, taking into account the nature of objects. The parallel use of mathematical models and real objects in a neural network for determining the coordinates of signals and their characteristics is proposed, which leads to an increase in accuracy for each type of object, the possibility of constructing intelligent control devices for outer space. Using the example of an experimental installation of two synchronously movable optoelectronic systems, the accuracy of combining images of objects in multiplexing systems from different digital sources is demonstrated.

Keywords: continuous wavelet transform, curves of coefficients of continuous wavelet transform, double wavelet transform, distance between objects, aspect of objects, resolution of superimposed objects, artificial neural network.

V. E. Makhov, V. V. Shirobokov, A. V. Emelyanov, A. I. Potapov (Mozhaisky Military Space Academy, St. Petersburg, Russia) E-mail: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра. , Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра. , Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра. , Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.  

1. Sviridov K. N. (2015). On achieving the maximum resolution of aerospace systems for remote sensing of the Earth (ERS). Raketno-kosmicheskoe priborostroenie i informatsionnye tekhnologii, pp. 489 – 499. Moscow: OAO RKS. [in Russian language]
2. Makhov V. E., Shirobokov V. V., Emelyanov A. V. (2020). Study of possibilities for light marker coordinate measuring with light field digital cameras. IOP Conference Series: Materials Science and Engineering, Vol. 918, (1). DOI 10.1088/1757-899X/918/1/012079.
3. Goritov A. N. (2018). Preprocessing of images in vision systems. Doklady TUSUR, Vol. 21, (4-1). [in Russian language] DOI 10.21293/1818-0442-2018-21-4-1-53-58.
4. Altynov A. E., Gruzinov V. V., Mishin I. V. (2017). Correlation analysis of aerospace images. Izvestiya vysshih uchebnyh zavedeniy. Geodeziya i aerofotosyemka, (1), pp. 34 – 40. [in Russian language]
5. Makhov V. E., Shaldaev S. E., Potapov A. I., Smorodinskiy Ya. G. (2020). Influence of Image Quality in Optoelectronic Systems on the Accuracy of Determination of Object Parameters under Study. Defektoskopiya, (7), pp. 28 – 43. [in Russian language] DOI 10.31857/S01303082200700 40.
6. Kučera Jan. (2014). Computational photography of light-field camera and application to panoramic photography. Department of Software and Computer Science Education Supervisor of the master thesis: Ing. Filip Šroubek, Ph.D. Study programme: Computer Science, Software Systems Specialization: Computer Graphics. Prague.
7. Ng R. (2006). Digital light field photography: A dissertation submitted to the department of computer science and the committee on graduate studies of Stanford university in partial fulfillment of the requirements for the degree of doctor of philosophy.
8. Bok Y., Jeon H.-G., Kweon I. S. (2017). Geometric Calibration of Micro-Lens-Based Light-Field Cameras using Line Features. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 39, (2), pp. 287 – 300. DOI 10.1109/TPAMI.2016.2541145.
9. Chui Ch. K. (1992). An Introduction to Wavelets. San Diego: Academic Press. DOI 10.2307/2153134
10. Yudin M. N., Farkov Yu. A., Filatov D. M. (2001). Introduction to wavelet analysis: educational and practical guide. Moscow: Moskovskaya geologorazvedochnaya akademiya. [in Russian language]
11. Voskoboynikov Yu. E. (2015). Wavelet filtering of signals and images (with examples in the MathCAD package). Novosibirskiy Gosudarstvenniy arhitekturno-stroitel'niy universitet (Sibstrin). Novosibirsk: NGASU (Sibstrin). [in Russian language]
12. Kozin E. V., Karmanov A. G., Karmanova N. A. (2019). Photogrammetry. Saint Petersburg: Universitet ITMO. [in Russian language]
13. Radkevich M. M., Evgrafov A. N. (Eds.), Makhov V. E. (2012). Investigation of the wavelet transform algorithm for determining the coordinates of light marks in dilatometry. Proceedings of the 2nd International Scientific and Practical Conference “Modern Mechanical Engineering. Science and education", pp. 490 – 499. Saint Petersburg: Izdatel'stvo Politekhnicheskogo universiteta. [in Russian language]
14. Makhov V. E., Potapov A. I., Shirobokov V. V., Emel'yanov A. V. (2021). Investigation of the accuracy of measuring the parameters of remote objects observed by an optoelectronic system with a light field recorder. Nauchno-tekhnicheskiy vestnik informatsionnyh tekhnologiy, mekhaniki i optiki, Vol. 21, (3), pp. 342 – 351. [in Russian language] DOI 10.17586/2226-1494-2021-21-3-342-351
15. Makhov V. E., Petrushenko V. M., Emel'yanov A. V. et al. (2021). Technology for the development of software algorithms for optoelectronic systems for observing remote objects. Vestnik komp'yuternyh i informatsionnyh tekhnologiy, Vol. 18, 208(10), pp. 10 – 21. [in Russian language] DOI 10.14489/vkit.2021.10.pp.010-021.
16. Travis J., Kring J. (2007). LabVIEW for Everyone: Graphical Programming Made Easy and Fun. 3rd ed. Prentice Hall.
17. Klinger T. (2003). Image processing with Labview and Imaq Vision. Prentice Hall Professional. (National Instruments Virtual Instrumentation Series).
18. Dobeshi I. (2001). Ten lectures on wavelets. Izhevsk: NITs Regulyarnaya i haoticheskaya dinamika. [in Russian language]
19. Makhov V., Shirobokov V., Petrushenko V. (2020). Methodology for constructing algorithms for determining the parameters of small-sized objects. Komponenty i tekhnologii, 225(4), pp. 110 – 114. [in Russian language]
20. Makhov V. E. (2010). The use of wavelet analysis algorithms in the study of the kinetics of the formation of powder firing coatings. Konstruktsii iz kompozitsionnyh materialov, (3), pp. 28 – 36. [in Russian language]
21. Makhov V. E., Shirobokov V. V., Emel'yanov A. V., Potapov A. I. (2020). Investigation of an optoelectronic system based on a telescope with a light field digital camera. Kontrol'. Diagnostika, Vol. 23, 269(11), pp. 4 – 13. [in Russian language] DOI 10.14489/td.2020.11.pp.004-013
22. Frolov V. N., Tupikov V. A., Pavlova V. A., Aleksandrov V. A. (2016). Methods of information combination of images in multichannel optoelectronic systems. Izvestiya TulGU. Tekhnicheskie nauki, (11), Part 3, pp. 95 – 104. [in Russian language]
23. Radkevich M. M., Evgrafov A. N. (Eds.), Makhov V. E., Repin O. S. (2012). Study of the possibilities of video monitoring systems based on National Instruments solutions on roll printing machines. Materials of the 2nd International Scientific and Practical Conference "Modern Mechanical Engineering", pp. 500 – 510. Saint Petersburg: Izdatel'stvo Politekhnicheskogo universiteta. [in Russian language]
24. Makhov V., Shirobokov V., Emel'yanov A. et al. (2022). Prospects for the development of optoelectronic systems with high spatial resolution. Komponenty i tekhnologii, (2), pp. 10 – 13. [in Russian language]

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