Directional variance-based algorithm for digital image smoothing
https://doi.org/10.17586/2226-1494-2025-25-1-78-86
Abstract
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.
Supporting agencies: I have heartfelt gratitude to the Computer Center staff for the aid that led to the completion of this research.
About the Author
Al-Ameen Zohair
ICT Research Unit, University of Mosul
Iraq
Iraq
Zohair Al-Ameen — PhD (Computer Science), Associate Professor, Researcher
Mosul, 41002
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Review
For citations:
Zohair A. Directional variance-based algorithm for digital image smoothing. Scientific and Technical Journal of Information Technologies, Mechanics and Optics. 2025;25(1):78-86. https://doi.org/10.17586/2226-1494-2025-25-1-78-86
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