THE USE OF Q-PREPARATION FOR AMPLITUDE FILTERING OF DISCRETED IMAGE
Leonid Timchenko
tumchenko_li@gsuite.duit.edu.uaState University of Infrastructure and Technology (Ukraine)
http://orcid.org/0000-0001-5056-5913
Natalia Kokriatskaia
State University of Infrastructure and Technology (Ukraine)
http://orcid.org/0000-0003-0090-3886
Mykhailo Rozvodiuk
Vinnytsia National Technical University (Ukraine)
http://orcid.org/0000-0002-0916-1172
Volodymyr Tverdomed
State University of Infrastructure and Technology (Ukraine)
http://orcid.org/0000-0002-0695-1304
Yuri Kutaev
State University of Infrastructure and Technology (Ukraine)
http://orcid.org/0000-0001-8025-8172
Saule Smailova
D.Serikbayev East Kazakhstan State Technical University (Kazakhstan)
http://orcid.org/0000-0002-8411-3584
Vladyslav Plisenko
State University of Infrastructure and Technology (Ukraine)
http://orcid.org/0000-0002-5970-2408
Liudmyla Semenova
State University of Infrastructure and Technology (Ukraine)
http://orcid.org/0000-0002-0904-3002
Dmytro Zhuk
State University of Infrastructure and Technology (Ukraine)
http://orcid.org/0000-0001-8951-5542
Abstract
The article was aimed at improving the amplitude filtering process of the sampled image through the use of generalized Q-preparation. The existing correlation algorithms for image preprocessing were analyzed and their advantages and disadvantages were identified. The process of amplitude filtering and the main methods of preprocessing with such filtering were considered. A method of amplitude filtering of images based on the generalized Q-transformation with the use of sum-difference preprocessing of images has been developed. The efficiency of this method was analyzed, and a variant of the scheme for the corresponding preprocessing of images was proposed. The efficiency of the method was confirmed by computer simulation.
Keywords:
amplitude filtering, generalized Q-preparation, correlation algorithmsReferences
Avrunin O. G., Nosova Y. V., Abdelhamid I. Y., Pavlov S. V., Shushliapina N. O., Bouhlal N. A., Harasim D.: Research active posterior rhinomanometry tomography method for nasal breathing determining violations. Sensors 21(24), 2021, 1–27.
DOI: https://doi.org/10.3390/s21248508
Google Scholar
Bochkarev A. M.: Correlation-Navigation Navigation Systems. Foreign radio electronics 9, 1981, 12–16.
Google Scholar
Cai Y., Liu Z., Wang H., Sun X.: Saliency-Based Pedestrian Detection in Far Infrared Images. IEEE Access 5, 2017, 5013–5019.
DOI: https://doi.org/10.1109/ACCESS.2017.2695721
Google Scholar
Dougherty E. R.: Digital Image Processing Methods. CRC Press, Boca Raton 2020.
DOI: https://doi.org/10.1201/9781003067054
Google Scholar
Gan W. S.: Signal Processing and Image Processing for Acoustical Imaging. Springer, Singapore 2020.
DOI: https://doi.org/10.1007/978-981-10-5550-8
Google Scholar
Image correlation analysis system. Cipher "Cyber" – Research report. Vinnitsa Polytechnic Institute N01890065739, Vinnitsa 1991.
Google Scholar
Kutaev Y. F.: Systemic correlation-extreme measurement of coordinates with generalized Q-preparation of images. VNTU, Vinnitsa 1989
Google Scholar
Nosova Y. V., Tymkovych M. Y., et al.: Peculiarities of pre-processing of tomographic images for segmentation of paranasal sinuses. IEEE 39th International Conference on Electronics and Nanotechnology, ELNANO 2019, 489–492.
DOI: https://doi.org/10.1109/ELNANO.2019.8783713
Google Scholar
Pavlov S. V., Vassilenko V. B., Saldan I. R., Vovkotrub D. V., Poplavskaya A. A., Kuzin O. O.: Methods of processing biomedical image of retinal macular region of the eye. Proc. of SPIE 9961, 2016, 99610X.
DOI: https://doi.org/10.1117/12.2237154
Google Scholar
Pogribnoi V. A.: Airborne signal processing systems. Kiev, Naukova Dumka 1984.
Google Scholar
Pratt W.: Digital image processing (Т. 1 & 2). Wiley, New York 1982.
Google Scholar
Sacerdoti F.: Digital Image Processing. In: Sacerdoti, F., Giordano, A., Cavaliere, C. (eds): Advanced Imaging Techniques in Clinical Pathology. Current Clinical Pathology. Humana Press, New York 2016.
DOI: https://doi.org/10.1007/978-1-4939-3469-0
Google Scholar
Surabhi N., Unnithan S.: Image Compression Techniques: A Review. IJDER 5(1), 2017, 585–589.
Google Scholar
Timchenko L. I., Kokriatskaia N. I. et al.: Analysis of computational processes of pyramidal and parallel-hierarchical processing of information. Proc. of SPIE 10808, 2018, 1080822.
Google Scholar
Timchenko L. I., Kokryatskaya N. I., Melnikov V. V., Kosenko G. L.: Method of forecasting energy center positions of laser beam spot images using a parallel hierarchical network for optical communication systems. J. Optical Engineering 52(5), 2013, 055003.
DOI: https://doi.org/10.1117/1.OE.52.5.055003
Google Scholar
Trishch R., Nechuiviter O., Vasilevskyi O., Dyadyura K., Tsykhanovska I., Yakovlev M.: Qualimetric method of assessing risks of low quality products. MM Science Journal 2021(4), 2021, 4769–4774.
DOI: https://doi.org/10.17973/MMSJ.2021_10_2021030
Google Scholar
Tulbure A., Tulbure A. A.: The use of image recognition systems in manufacturing processes. IEEE International Conference on Automation, Quality and Testing, Robotics. Cluj-Napoca 2018.
Google Scholar
Tymkovych M., Avrunin O. et al.: Ice crystals microscopic images segmentation based on active contours. IEEE 39th International Conference on Electronics and Nanotechnology, ELNANO 2019, 493–496.
DOI: https://doi.org/10.1109/ELNANO.2019.8783332
Google Scholar
Vasilevskyi O., Koval M., Kravets S.: Indicators of reproducibility and suitability for assessing the quality of production services. Acta IMEKO 10(4), 2021, 54–61.
DOI: https://doi.org/10.21014/acta_imeko.v10i4.814
Google Scholar
Vasilevskyi O., Kulakov P., Kompanets D., Lysenko O. et al.: New approach to assessing the dynamic uncertainty of measuring devices. Proc. of SPIE 10808, 2018, 108082E.
Google Scholar
Vyatkin S. I., Romanyuk S. A. et al.: Using lights in a volume-oriented rendering. Proc. of SPIE 10445, 2017, 104450U.
DOI: https://doi.org/10.1117/12.2280982
Google Scholar
Wójcik W., Pavlov S., Kalimoldayev M.: Information Technology in Medical Diagnostics II. Taylor & Francis Group, CRC Press, Balkema book, London 2019.
DOI: https://doi.org/10.1201/9780429057618
Google Scholar
Zabolotna N. I., Pavlov S. V., Ushenko A. G., Karachevtsev A. O., Savich V. O. et al.: System of the phase tomography of optically anisotropic polycrystalline films of biological fluids. Proc. of SPIE 9166, 2014, 916616.
DOI: https://doi.org/10.1117/12.2061116
Google Scholar
Authors
Leonid Timchenkotumchenko_li@gsuite.duit.edu.ua
State University of Infrastructure and Technology Ukraine
http://orcid.org/0000-0001-5056-5913
Authors
Natalia KokriatskaiaState University of Infrastructure and Technology Ukraine
http://orcid.org/0000-0003-0090-3886
Authors
Mykhailo RozvodiukVinnytsia National Technical University Ukraine
http://orcid.org/0000-0002-0916-1172
Authors
Volodymyr TverdomedState University of Infrastructure and Technology Ukraine
http://orcid.org/0000-0002-0695-1304
Authors
Yuri KutaevState University of Infrastructure and Technology Ukraine
http://orcid.org/0000-0001-8025-8172
Authors
Saule SmailovaD.Serikbayev East Kazakhstan State Technical University Kazakhstan
http://orcid.org/0000-0002-8411-3584
Authors
Vladyslav PlisenkoState University of Infrastructure and Technology Ukraine
http://orcid.org/0000-0002-5970-2408
Authors
Liudmyla SemenovaState University of Infrastructure and Technology Ukraine
http://orcid.org/0000-0002-0904-3002
Authors
Dmytro ZhukState University of Infrastructure and Technology Ukraine
http://orcid.org/0000-0001-8951-5542
Statistics
Abstract views: 192PDF downloads: 159
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Most read articles by the same author(s)
- Yosyp Bilynsky, Aleksandr Nikolskyy, Viktor Revenok, Vasyl Pogorilyi, Saule Smailova, Oksana Voloshina, Saule Kumargazhanova, CONVOLUTIONAL NEURAL NETWORKS FOR EARLY COMPUTER DIAGNOSIS OF CHILD DYSPLASIA , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 13 No. 2 (2023)
- Borys Mokin, Vitalii Mokin, Oleksandr Mokin, Orken Mamyrbaev, Saule Smailova, THE SYNTHESIS OF MATHEMATICAL MODELS OF NONLINEAR DYNAMIC SYSTEMS USING VOLTERRA INTEGRAL EQUATION , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 12 No. 2 (2022)
- Maksym Tymkovych, Oleg Avrunin, Karina Selivanova, Alona Kolomiiets, Taras Bednarchyk, Saule Smailova, CORRESPONDENCE MATCHING IN 3D MODELS FOR 3D HAND FITTING , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 14 No. 1 (2024)
- Leonid Timchenko, Natalia Kokriatskaia, Volodymyr Tverdomed, Natalia Kalashnik, Iryna Shvarts, Vladyslav Plisenko, Dmytro Zhuk, Saule Kumargazhanova, LOCAL DIFFERENCE THRESHOLD LEARNING IN FILTERING NORMAL WHITE NOISE , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 13 No. 2 (2023)
- Yelena Blinayeva, Saule Smailova, MODELING OF PROCESSES IN CRUDE OIL TREATED WITH LOW-FREQUENCY SOUNDS , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 9 No. 2 (2019)
- Volodymyr Mykhalevych, Yurii Dobraniuk, Victor Matviichuk, Volodymyr Kraievskyi, Oksana Тiutiunnyk, Saule Smailova, Ainur Kozbakova, A COMPARATIVE STUDY OF VARIOUS MODELS OF EQUIVALENT PLASTIC STRAIN TO FRACTURE , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 13 No. 1 (2023)
- Leonid Timchenko, Natalia Kokriatskaya, Volodymyr Tverdomed, Oleksandr Stetsenko, Valentina Kaplun, Oleg K. Kolesnytskyj, Oleksandr Reshetnik, Saule Smailova, Ulzhalgas Zhunissova, SEGMENTATION OF MULTIGRADATION IMAGES BASED ON SPATIAL CONNECTIVITY FEATURES , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 13 No. 3 (2023)
- Kateryna Barandych, Sergii Vysloukh, Grygoriy Tymchyk, Oleksandr Murashchenko, Saule Smailova, Saule Kumargazhanova, OPTIMIZATION OF PARTS CUTTING PROCESS PARAMETERS WORKING IN CONDITIONS OF CYCLIC LOADS , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 13 No. 3 (2023)
- Leonid Timchenko, Natalia Kokriatska, Volodymyr Tverdomed, Iryna Yepifanova, Yurii Didenko, Dmytro Zhuk, Maksym Kozyr, Iryna Shakhina, ARCHITECTURAL AND STRUCTURAL AND FUNCTIONAL FEATURES OF THE ORGANIZATION OF PARALLEL-HIERARCHICAL MEMORY , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 14 No. 1 (2024)
- Nataliia Kozan, Oleksandr Saleha, Olexander Dubolazov, Yuriy Ushenko, Iryna Soltys, Oleksandr Ushenko, Oleksandr Olar, Victor Paliy, Saule Smailova, POLARIZATION-CORRELATION MAPPING OF MICROSCOPIC IMAGES OF BIOLOGICAL TISSUES OF DIFFERENT MORPHOLOGICAL STRUCTURE , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 14 No. 3 (2024)
