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Image Denoising via the Adaptive Rank-Cluster Filter

2026-08-15 16:05:16
Dmitry Pozdnyakov
arXiv_CV
       
Abstract

A spatial-local image-denoising filter is proposed, and its performance metrics are evaluated in comparison with baseline filtering algorithms, including the median, adaptive median, Gaussian, bilateral, Wiener, anisotropic diffusion, and non-local means. The developed filter is based on aligning the intensity value of the central pixel in a 3x3 window with the statistical majority intensity of one of the two clusters formed by optimal Otsu's partitioning of a pixel set sorted by intensity and trimmed to seven elements. This is followed by a fuzzy fusion of the calculated value with the median intensity of the pixels within the window. The proposed filter demonstrates the highest robustness to variations in image noise levels, particularly when processing mixed noise consisting of salt-and-pepper impulse noise and additive Gaussian noise in various proportions

Abstract (translated)

URL

https://arxiv.org/abs/2608.15298

PDF

https://arxiv.org/pdf/2608.15298.pdf

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