Digital three-stage recursive-separable image processing filter with variable sizes of scanning multielement aperture
https://doi.org/10.32362/2500-316X-2024-12-6-48-58
EDN: NZQPFH
Abstract
Objectives. The main aim of digital image processing is to increase clarity while maintaining image quality and eliminate noise. However, the amount of information contained in digital image files is growing year after year. This circumstance negatively affects processing time, critical for systems with high load requirements on the computing platform. In this regard, the use of digital filters which enable a reduction to the processing time of incoming data is important. In order to resolve this issue, adaptive filters with different sizes of multielement processing aperture are being developed to improve image clarity and preserve image details. Filters with adaptive properties are able to change their parameters during data processing, and provide maximum performance as the aperture size increases. The aim of the work is to develop a type of recursively separable digital filter with variable sizes of a scanning multielement aperture which allows the number of computational operations to be reduced while maintaining the efficiency of filtering input data (images).
Methods. The work used recursive-separable methods and algorithms to construct digital filters.
Results. An algorithm for the recursive-separable implementation of a digital filter is described, and the final view of the processing aperture and its three-dimensional appearance are presented. In order to evaluate the performance of the filter, a comparison of the developed algorithm with the classical two-dimensional convolution algorithm was carried out. The experiment was performed using images of various sizes and consisted of determining the time spent on the process of processing the test image. The study established that the processing time of a test image using the developed filter is on average 5 times less than the time taken by the classical two-dimensional convolution algorithm. The optimal coefficients for magnifying the central element and raising the positive part of the aperture of a digital filter were determined, enabling the efficiency of its use to be enabled.
Conclusions. The studies show the effectiveness of using the developed recursive-separable two-dimensional filter to improve image clarity and reduce the time spent on processing.
Keywords
About the Authors
A. V. KamenskiyRussian Federation
Andrey V. Kamenskiy, Cand. Sci. (Eng.), Associate Professor, Department of Television and Control
40, Lenina pr., Tomsk, 634050
Scopus Author ID 57191031758;
ResearcherID AAX-9780-2021
Competing Interests:
T. M. Akaeva
Russian Federation
Tatyana M. Akaeva, Postgraduate Student, Department of Television and Control
40, Lenina pr., Tomsk, 634050
Scopus Author ID 58511241300;
ResearcherID GZK-2362-2022
D. A. Grebenshchikova
Russian Federation
Darya A. Grebenshchikova, Student, Department of Television and Control
40, Lenina pr., Tomsk, 634050
References
1. REFERENCES
2. Groshev I.V., Korol’kov V.I. Sistemy tekhnicheskogo zreniya i obrabotki izobrazhenii (Technical Vision and Image Processing Systems). Moscow: RUDN; 2008. 212 p. (in Russ.).
3. Abramov I.A., Kravchenko E.N. Multithreaded realization of the algorithm of local image filtering. Vestnik Penzenskogo gosudarstvennogo universiteta = Vestnik of Penza State University. 2016;3(15):66–71 (in Russ.).
4. Turulin I.I. Osnovy teorii rekursivnykh KIKh-fil’trov ( Recursive FIR Filters Theory Base). Taganrog: Southern Federal University; 2016. 264 p. (in Russ.).
5. Ifeachor E.C., Jervis B.W. Tsifrovaya obrabotka signalov. Prakticheskii podkhod (Digital Signal Processing: A Practical Approach): transl. from Engl. Moscow: Williams; 2004. 992 p. (in Russ.). [Ifeachor E.C., Jervis B.W. Digital Signal Processing: A Practical Approach. Prentice Hall; 2001. 933 p.]
6. Gol’denberg L.M., Matyushkin B.D., Polyak M.N. Tsifrovaya obrabotka signalov ( Digital Signal Processing). Moscow: Radio i cvyaz’; 1990. 256 p. (in Russ.).
7. Kuryachii M.I., Gel’tser A.A., Abenov R.R., et al. Tsifrovaya obrabotka signalov (Digital Signal Processing). Tomsk: Tomsk State Univ. of Control Systems and Radioelectronics; 2018. 234 p. (in Russ.).
8. Lukin A. Vvedenie v tsifrovuyu obrabotku signalov (Introduction to Digital Signal Processing). Moscow: MSU, Laboratory of Computer Graphics and Multimedia; 2002. 44 p. (in Russ.).
9. Matveev Yu.N., Simonchik K.K., Tropchenko A.Yu., et al. Tsifrovaya obrabotka signalov ( Digital Signal Processing). St. Petersburg: ITMO; 2013. 166 p. (in Russ.).
10. Bondina N.N., Murarov R.Yu. Adaptive algorithms of filtration and contrast changes of image. Vestnik Natsional’nogo tekhnicheskogo universiteta “Khar’kovskii politekhnicheskii institute”. Seriya: Informatika i modelirovanie = Bulletin of the National Technical University Kharkov Polytechnic Institute. Series: Informatics and Modeling. 2014;35(1078):35–42 (in Russ.).
11. Kamenskiy A.V., Rylov K.A., Borodina N. Digital anti-aliasing trapezoidal recursively separable image processing filter with resizable scanning multielement aperture. Omskii nauchnyi vestnik = Omsk Scientific Bulletin. 2024;1(189):127–136 (in Russ.). https://doi.org/10.25206/1813-8225-2024-189-127-136
12. Say S.V., Kamenskiy A.V., Kuryachiy M.I. Sovremennye metody analiza i povyshenie kachestva tsifrovykh izobrazhenii (Modern Methods of Analyzing and Improving the Quality of Digital Images: monograph). Khabarovsk: Pacific National University; 2020. 173 p. (in Russ.).
13. Kamenskiy A.V. High-speed recursive-separable image processing filters. Computer Optics. 2022;46(4):659–665. http://doi.org/10.18287/2412-6179-CO-1063
14. Akaeva T.M., Kamenskiy A.V., Strumilova M.A. Recursive-separable filter image enhancement. Voprosy radioelektroniki. Seriya: Tekhnika televideniya = Questions of Radio Electronics. Series: TV Technique. 2023;1:138–145 (in Russ.).
15. Gonzalez R., Woods R. Tsifrovaya obrabotka izobrazhenii ( Digital Image Processing): transl. from Engl. Moscow: Tekhnosfera; 2019. 1104 p. (in Russ.). [Gonzalez R., Woods R. Digital Image Processing. Pearson/Prentice Hall; 2008. 954 p.]
16. Malanin M.Yu., Kamenskiy A.V., Kuryachiy M.I. Measurement of resolution and clarity of television images. In: Optoelectronic Devices and Devices in Systems of Pattern Recognition, Image and Symbolic Information Processing: Collection of materials of the 12th International Scientific and Technical Conference. Kursk; 2015. P. 235–237 (in Russ.).
17. Movchan A.K., Kapustin V.V., Kuryachiy M.I. Methods and means of tomographic vision of space by active-pulse television measuring systems. Proceedings of the International Conference on Computer Graphics and Vision “Graficon”. 2018;28:222–225. http://www.graphicon.ru/html/2018/papers/proceedings.pdf
18. Zaytseva E.V. Integral and spectral sensitivity assessment of the active-pulse television systems. In: 2016 Dynamics of Systems, Mechanisms and Machines (Dynamics). 2016:7819115. https://doi.org/10.1109/Dynamics.2016.7819115
Supplementary files
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1. Images before (a) and after (b) processing with the filter with optimal coefficient А1 | |
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Type | Исследовательские инструменты | |
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Indexing metadata ▾ |
- The aim of the work is to develop a type of recursively separable digital filter with variable sizes of a scanning multi-element aperture which allows the number of computational operations to be reduced while maintaining the efficiency of filtering input data (images).
- An algorithm for the recursive-separable implementation of a digital filter is described, and the final view of the processing aperture and its three-dimensional appearance are presented.
- In order to evaluate the performance of the filter, a comparison of the developed algorithm with the classical two-dimensional convolution algorithm was carried out.
- The study established that the processing time of a test image using the developed filter is on average 5 times less than the time taken by the classical two-dimensional convolution algorithm.
Review
For citations:
Kamenskiy A.V., Akaeva T.M., Grebenshchikova D.A. Digital three-stage recursive-separable image processing filter with variable sizes of scanning multielement aperture. Russian Technological Journal. 2024;12(6):48-58. https://doi.org/10.32362/2500-316X-2024-12-6-48-58. EDN: NZQPFH