Open AccessAdaptive frequency median filter for the salt and pepper denoising problem
Author(s) -
Erkan Uğur,
Enginoğlu Serdar,
Thanh Dang N.H.,
Hieu Le Minh
Publication year - 2020
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2019.0398
Subject(s) - median filter , pixel , salt and pepper noise , noise reduction , mathematics , artificial intelligence , noise (video) , non local means , filter (signal processing) , adaptive filter , computer science , pattern recognition (psychology) , statistics , computer vision , image denoising , image processing , algorithm , image (mathematics)
In this article, the authors propose an adaptive frequency median filter (AFMF) to remove the salt and pepper noise. AFMF uses the same adaptive condition of adaptive median filter (AMF). However, AFMF employs frequency median to restore grey values of the corrupted pixels instead of the median of AMF. The frequency median can exclude noisy pixels from evaluating a grey value of the centre pixel of the considered window, and it focuses on the uniqueness of grey values. Hence, the frequency median produces a grey value closer to the original grey value than the one by the median of AMF. Therefore, AFMF outperforms AMF. In experiments, the authors tested the proposed method on a variety of natural images of the MATLAB library, as well as the TESTIMAGES data set. Additionally, they also compared the denoising results of AFMF to the ones of other state‐of‐the‐art denoising methods. The results showed that AFMF denoises more effectively than other methods.