Open AccessContext‐based prediction filtering of impulse noise images
Author(s) -
Gellert Arpad,
Brad Remus
Publication year - 2016
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.2015.0702
Subject(s) - impulse noise , grayscale , pixel , noise reduction , computer science , artificial intelligence , context (archaeology) , computer vision , median filter , noise (video) , filter (signal processing) , pattern recognition (psychology) , non local means , impulse (physics) , image denoising , image (mathematics) , image processing , paleontology , physics , quantum mechanics , biology
A new image denoising method for impulse noise in greyscale images using a context‐based prediction scheme is presented. The algorithm replaces the noisy pixel with the value occurring with the highest frequency, in the same context as the replaceable pixel. Since it is a context‐based technique, it preserves the details in the filtered images better than other methods. In the aim of validation, the authors have compared the proposed method with several existing denoising methods, many of them being outperformed by the proposed filter.