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Article detail · 2021

Different Adaptive Modified Riesz Mean Filter For High-Density Salt-and-Pepper Noise Removal in Grayscale Images

Journal

European Journal of Science and Technology

ISSN 2148-2683

YÖKSİS OpenAlex Open access · diamond TR Index Citations 14 Percentile 74.4% FWCI 1.0
Year
2021
Type
article

Data source split

  • YÖKSİS YÖKSİS article record
  • YÖKSİS venue European Journal of Science and Technology
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

Turkish

This paper proposes a new filter, Different Adaptive Modified Riesz Mean Filter (DAMRmF), for high-density salt-and-pepper noise (SPN) removal.DAMRmF operationalizes a pixel weight function and adaptivity condition of Adaptive Median Filter (AMF).In the simulation, the proposed filter is compared with Adaptive Frequency Median Filter (AFMF), Three-Values-Weighted Method (TVWM), Unbiased Weighted Mean Filter (UWMF), Different Applied Median Filter (DAMF), Adaptive Weighted Mean Filter (AWMF), Adaptive Cesáro Mean Filter (ACmF), Adaptive Riesz Mean Filter (ARmF), and Improved Adaptive Weighted Mean Filter (IAWMF) for 20 traditional test images with noise levels from 60% to 90%.The results show that DAMRmF outperforms the state-of-the-art filters in terms of Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) values.Moreover, DAMRmF also performs better than the state-of-the-art filters concerning mean PSNR and SSIM results.We finally discuss DAMRmF for further research.

Topics

  • Image and Signal Denoising Methods
  • PAPR reduction in OFDM
  • High voltage insulation and dielectric phenomena

Primary topic Image and Signal Denoising Methods

Authors

  1. SAMET MEMİŞ BANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİ
  2. UĞUR ERKAN ANKARA ÜNİVERSİTESİ