Proceedings of International Conference on Applied Innovation in IT  ·  2026/06/12  ·  Vol. 14  ·  Issue 3  ·  pp. 177–186
Image Smoothing Methods for Structure Preservation in Computer Vision
Manar Abdulkareem Al-Abaji and Mohammed Hazim Alkawaz
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Abstract
Image smoothing is a fundamental pre-processing step in multimedia and computer vision applications, as it suppresses texture and high-frequency details to facilitate subsequent processing and analysis. A smoothed image is essential for many image processing tasks, such as sharpening, edge detection, abstraction, and detail enhancement. However, a critical challenge in image smoothing lies in balancing the attenuation of high-frequency details with the preservation of prominent structural information. Many existing smoothing methods struggle to achieve this balance, often resulting in excessive blurring, loss of important details, or the introduction of undesired artifacts. To address these limitations, this paper proposes a novel image smoothing method based on the Fractional Riesz Derivative. The proposed approach is designed to smooth color images while effectively preserving their essential structural features. Its performance assessed with over 330k of diverse color images from COCO data set, compared with other six state-of-the-art smoothing techniques in order to highlight the proposed method’s effectiveness. Experimental results show that the proposed method outperforms to other methods through three quantitative evaluation metrics.
Keywords
Edge Detection Fractional Riesz Derivative Structure Preserving Image Smooth Multi-Channel Smoothing.
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