ZASTOSOWANIE Q-PREPARACJI DO FILTROWANIA AMPLITUDOWEGO ZDYSKRETYZOWANEGO OBRAZU

Leonid Timchenko

tumchenko_li@gsuite.duit.edu.ua
State University of Infrastructure and Technology (Ukraina)
http://orcid.org/0000-0001-5056-5913

Natalia Kokriatskaia


State University of Infrastructure and Technology (Ukraina)
http://orcid.org/0000-0003-0090-3886

Mykhailo Rozvodiuk


Vinnytsia National Technical University (Ukraina)
http://orcid.org/0000-0002-0916-1172

Volodymyr Tverdomed


State University of Infrastructure and Technology (Ukraina)
http://orcid.org/0000-0002-0695-1304

Yuri Kutaev


State University of Infrastructure and Technology (Ukraina)
http://orcid.org/0000-0001-8025-8172

Saule Smailova


D.Serikbayev East Kazakhstan State Technical University (Kazachstan)
http://orcid.org/0000-0002-8411-3584

Vladyslav Plisenko


State University of Infrastructure and Technology (Ukraina)
http://orcid.org/0000-0002-5970-2408

Liudmyla Semenova


State University of Infrastructure and Technology (Ukraina)
http://orcid.org/0000-0002-0904-3002

Dmytro Zhuk


State University of Infrastructure and Technology (Ukraina)
http://orcid.org/0000-0001-8951-5542

Abstrakt

Artykuł miał na celu usprawnienie procesu filtrowania amplitudy zdyskretyzowanego obrazu za pomocą uogólnionej Q-preparacji. Przeanalizowano istniejące algorytmy korelacji do wstępnego przetwarzania obrazu i określono ich wady i zalety. Omówiono proces filtracji amplitudowej oraz główne metody wstępnego przetwarzania z taką filtracją. Opracowano metodę filtrowania amplitudowego obrazów w oparciu o uogólnioną transformację Q z wykorzystaniem wstępnego przetwarzania obrazów na podstawie różnic sumy. Przeanalizowano skuteczność tej metody i zaproponowano wariant odpowiedniego schematu wstępnego przetwarzania obrazu. Skuteczność metody została potwierdzona symulacją komputerową.


Słowa kluczowe:

filtrowanie amplitudy, uogólniona Q-preparacja, algorytmy korelacji

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


Opublikowane
2022-12-30

Cited By / Share

Timchenko, L., Kokriatskaia, N., Rozvodiuk, M., Tverdomed, V., Kutaev, Y., Smailova, S., … Zhuk, D. (2022). ZASTOSOWANIE Q-PREPARACJI DO FILTROWANIA AMPLITUDOWEGO ZDYSKRETYZOWANEGO OBRAZU. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 12(4), 41–46. https://doi.org/10.35784/iapgos.3246

Autorzy

Leonid Timchenko 
tumchenko_li@gsuite.duit.edu.ua
State University of Infrastructure and Technology Ukraina
http://orcid.org/0000-0001-5056-5913

Autorzy

Natalia Kokriatskaia 

State University of Infrastructure and Technology Ukraina
http://orcid.org/0000-0003-0090-3886

Autorzy

Mykhailo Rozvodiuk 

Vinnytsia National Technical University Ukraina
http://orcid.org/0000-0002-0916-1172

Autorzy

Volodymyr Tverdomed 

State University of Infrastructure and Technology Ukraina
http://orcid.org/0000-0002-0695-1304

Autorzy

Yuri Kutaev 

State University of Infrastructure and Technology Ukraina
http://orcid.org/0000-0001-8025-8172

Autorzy

Saule Smailova 

D.Serikbayev East Kazakhstan State Technical University Kazachstan
http://orcid.org/0000-0002-8411-3584

Autorzy

Vladyslav Plisenko 

State University of Infrastructure and Technology Ukraina
http://orcid.org/0000-0002-5970-2408

Autorzy

Liudmyla Semenova 

State University of Infrastructure and Technology Ukraina
http://orcid.org/0000-0002-0904-3002

Autorzy

Dmytro Zhuk 

State University of Infrastructure and Technology Ukraina
http://orcid.org/0000-0001-8951-5542

Statystyki

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