Development of digital image processing algorithms based on the Winograd method in general form and analysis of their computational complexity

The fast increase of the amount of quantitative and qualitative characteristics of digital visual data calls for the improvement of the performance of modern image processing devices. This article proposes new algorithms for 2D digital image processing based on the Winograd method in a general form....

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Главные авторы:	Lyakhov, P. A., Ляхов, П. А., Nagornov, N. N., Нагорнов, Н. Н., Semyonova, N. F., Семенова, Н. Ф., Abdulsalyamova, A. S., Абдулсалямова, А. Ш.
Формат:	Статья
Язык:	Russian
Опубликовано:	2023
Темы:	Winograd method Computational complexity Digital image processing Digital filtering
Online-ссылка:	https://dspace.ncfu.ru/handle/20.500.12258/23477
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id	ir-20.500.12258-23477
record_format	dspace
spelling	ir-20.500.12258-234772025-02-11T13:30:14Z Development of digital image processing algorithms based on the Winograd method in general form and analysis of their computational complexity Lyakhov, P. A. Ляхов, П. А. Nagornov, N. N. Нагорнов, Н. Н. Semyonova, N. F. Семенова, Н. Ф. Abdulsalyamova, A. S. Абдулсалямова, А. Ш. Winograd method Computational complexity Digital image processing Digital filtering The fast increase of the amount of quantitative and qualitative characteristics of digital visual data calls for the improvement of the performance of modern image processing devices. This article proposes new algorithms for 2D digital image processing based on the Winograd method in a general form. An analysis of the obtained results showed that the use of the Winograd method reduces the computational complexity of image processing by up to 84 % compared to the traditional direct digital filtering method depending on the filter parameters and image fragments, while not affecting the quality of image processing. The resulting Winograd method transformation matrices and the algorithms developed can be used in image processing systems to improve the performance of the modern microelectronic devices that carry out image denoising, compression, and pattern recognition. Research directions that show promise for further research include hardware implementation on a field-programmable gate array and application-specific integrated circuit, development of algorithms for digital image processing based on the Winograd method in a general form for a 1D wavelet filter bank and for stride convolution used in convolutional neural networks. 2023-05-12T12:54:29Z 2023-05-12T12:54:29Z 2023 Статья Lyakhov P.A., Nagornov N.N., Semyonova N.F., Abdulsalyamova A.S. Development of digital image processing algorithms based on the Winograd method in general form and analysis of their computational complexity // Computer Optics. - 2023. - 47 (1), pp. 68-78. - DOI: 10.18287/2412-6179-CO-1146 http://hdl.handle.net/20.500.12258/23477 ru Computer Optics application/pdf application/pdf
institution	СКФУ
collection	Репозиторий
language	Russian
topic	Winograd method Computational complexity Digital image processing Digital filtering
spellingShingle	Winograd method Computational complexity Digital image processing Digital filtering Lyakhov, P. A. Ляхов, П. А. Nagornov, N. N. Нагорнов, Н. Н. Semyonova, N. F. Семенова, Н. Ф. Abdulsalyamova, A. S. Абдулсалямова, А. Ш. Development of digital image processing algorithms based on the Winograd method in general form and analysis of their computational complexity
description	The fast increase of the amount of quantitative and qualitative characteristics of digital visual data calls for the improvement of the performance of modern image processing devices. This article proposes new algorithms for 2D digital image processing based on the Winograd method in a general form. An analysis of the obtained results showed that the use of the Winograd method reduces the computational complexity of image processing by up to 84 % compared to the traditional direct digital filtering method depending on the filter parameters and image fragments, while not affecting the quality of image processing. The resulting Winograd method transformation matrices and the algorithms developed can be used in image processing systems to improve the performance of the modern microelectronic devices that carry out image denoising, compression, and pattern recognition. Research directions that show promise for further research include hardware implementation on a field-programmable gate array and application-specific integrated circuit, development of algorithms for digital image processing based on the Winograd method in a general form for a 1D wavelet filter bank and for stride convolution used in convolutional neural networks.
format	Статья
author	Lyakhov, P. A. Ляхов, П. А. Nagornov, N. N. Нагорнов, Н. Н. Semyonova, N. F. Семенова, Н. Ф. Abdulsalyamova, A. S. Абдулсалямова, А. Ш.
author_facet	Lyakhov, P. A. Ляхов, П. А. Nagornov, N. N. Нагорнов, Н. Н. Semyonova, N. F. Семенова, Н. Ф. Abdulsalyamova, A. S. Абдулсалямова, А. Ш.
author_sort	Lyakhov, P. A.
title	Development of digital image processing algorithms based on the Winograd method in general form and analysis of their computational complexity
title_short	Development of digital image processing algorithms based on the Winograd method in general form and analysis of their computational complexity
title_full	Development of digital image processing algorithms based on the Winograd method in general form and analysis of their computational complexity
title_fullStr	Development of digital image processing algorithms based on the Winograd method in general form and analysis of their computational complexity
title_full_unstemmed	Development of digital image processing algorithms based on the Winograd method in general form and analysis of their computational complexity
title_sort	development of digital image processing algorithms based on the winograd method in general form and analysis of their computational complexity
publishDate	2023
url	https://dspace.ncfu.ru/handle/20.500.12258/23477
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Development of digital image processing algorithms based on the Winograd method in general form and analysis of their computational complexity

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