Adaptive frequency median filter for the salt and pepper denoising problem


ERKAN U., ENGİNOĞLU S., Thanh D. N. H. , Le Minh Hieu L. M. H.

IET IMAGE PROCESSING, vol.14, no.7, pp.1291-1302, 2020 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 14 Issue: 7
  • Publication Date: 2020
  • Doi Number: 10.1049/iet-ipr.2019.0398
  • Journal Name: IET IMAGE PROCESSING
  • Journal Indexes: Science Citation Index Expanded, Scopus, Academic Search Premier, PASCAL, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.1291-1302
  • Keywords: adaptive filters, image denoising, median filters, adaptive frequency median filter, pepper denoising problem, AFMF, pepper noise, adaptive condition, adaptive median filter, AMF, original grey value, NOISE, REMOVAL, ALGORITHM, DENSITY

Abstract

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.