NAMF: A Nonlocal Adaptive Mean Filter for Removal of Salt-and-Pepper Noise
Author(s) -
Houwang Zhang,
Yuan Zhu,
Hanying Zheng
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/4127679
Subject(s) - salt and pepper noise , median filter , noise (video) , pixel , filter (signal processing) , computer science , noise reduction , pepper , mathematics , adaptive filter , artificial intelligence , computer vision , algorithm , image (mathematics) , image processing , computer security
In this paper, a novel algorithm called a Nonlocal Adaptive Mean Filter (NAMF) for removing salt-and-pepper (SAP) noise from corrupted images is presented. We employ an efficient window detector with adaptive size to detect the noise. The noisy pixel is then replaced by the combination of its neighboring pixels, and finally, a SAP noise based nonlocal mean filter is used to reconstruct the intensity values of noisy pixels. Extensive experimental results demonstrate that NAMF can obtain better performance in terms of quality for restoring images at all levels of SAP noise.
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