ntvНаучно-технический вестник информационных технологий, механики и оптикиScientific and Technical Journal of Information Technologies, Mechanics and Optics2226-14942500-0373Университет ИТМО10.17586/2226-1494-2025-25-1-78-86ntv-423Research ArticleКОМПЬЮТЕРНЫЕ СИСТЕМЫ И ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИCOMPUTER SCIENCEАлгоритм сглаживания цифровых изображений на основе дисперсии направленийDirectional variance-based algorithm for digital image smoothinghttps://orcid.org/0000-0003-3630-2134ЗохаирАль-АминZohairAl-Ameen

Зохаир Аль-Амин — PhD (компьютерные технологии), доцент, исследователь

Мосул, 41002

Zohair Al-Ameen — PhD (Computer Science), Associate Professor, Researcher

Mosul, 41002

qizohair@uomosul.edu.iqОтделение информационных технологий Университета МосулаИракICT Research Unit, University of MosulIraq2025280220252517886Copyright © Зохаир А., 20252025Зохаир А.Zohair A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://ntv.elpub.ru/jour/article/view/423

Технология сглаживания изображений применяется при обработке изображений. Использование данной технологии ослабляет текстуру и ненужные высокочастотные компоненты, обеспечивает получение гладкого изображения с сохраненной структурой для облегчения последующих операций корректировки или анализа. Получение сглаженных изображений требуется во многих приложениях при обработке, например, High Dynamic Range изображений, при усилении деталей, повышении резкости, обнаружении краев, стилизации, абстракции и т. д. При этом, не все существующие методы сглаживания изображений успешно справляются с поставленной задачей. В результате могут возникнуть нежелательные проблемы, такие как удаление существенных деталей, введение чрезмерного размытия, дефекты обработки, ореолы и другие артефакты. В работе представлен новый алгоритм, который эффективно сглаживает изображение. Алгоритм основан на концепции направленных дисперсий (Directional Variances, DV) для минимизации энергии и получения баланса между сохранением структуры и гладкостью. С помощью концепции DV представленный алгоритм итеративно сглаживает изображение, диффузии, осуществляет регуляризацию и минимизацию энергии. Выполненная оценка полученных результатов на различных изображениях показала эффективность разработанного алгоритма. Алгоритм на основе DV обладает превосходными возможностями сглаживания изображений, сохраняя при этом структурные детали, что делает его ценным инструментом для приложений, применяемых в области цифровой обработки изображений.

Image smoothing is vital in image processing as it attenuates the texture and unnecessary high-frequency components and provides a smooth image with a preserved structure to facilitate subsequent operations or analysis. Smoothed images are required in many image processing applications, such as details boost, sharpening, High Dynamic Range imaging, edge detection, stylization, abstraction, etc. Still, not all existing smoothing methods are successful in this task, as some undesirable problems may be introduced, such as removing significant details, introducing excessive blurring, processing flaws, halos, and other artifacts. Thus, the opportunity still stands to provide a new algorithm that smooths an image efficiently. This study concisely explores smoothing via the Directional Variances (DV) concept. The proposed algorithm leverages the DV concept to minimize energy, seeking a balance between essential structural preservation and smoothness. The proposed algorithm iteratively smooths the image using DV, diffusion, regularization, and energy minimization. A thorough evaluation is conducted on diverse images, showcasing the effectiveness of the developed algorithm. The results demonstrate that the developed DV-based algorithm has superb abilities in smoothing different images while preserving structural details, making it a valuable tool for various applications in digital image processing.

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The authors declare that there are no conflicts of interest present.