A Recursive Mean Filter for Image Denoising
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Tarih
2019
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this article, we propose a Recursive Mean Filter (RMF) to remove the salt-and-pepper noise (SPN). We compare RMF with similar methods such as Decision Based Algorithm (DBA), Modified Decision-Based Unsymmetric Trimmed Median Filter (MDBUTMF), and Noise Adaptive Fuzzy Switching Median Filter (NAFSMF). In the experiments, we implement the test on 15 native images of the MATLAB library. To assess the denoising quality, we consider the following noise densities (noise levels): 10%, 30%, 50%, 70%, 90%; and use the well-known two quality metrics: Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM). The results show that RMF removes the noise effectively and competes with other state-of-the-art denoising methods.
Açıklama
International Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 21-22, 2019 -- Inonu Univ, Malatya, TURKEY
Anahtar Kelimeler
Salt-and-pepper noise, Non-linear functions, Noise removal, Matrix algebra, Image denoising
Kaynak
2019 International Conference on Artificial Intelligence and Data Processing (Idap 2019)
WoS Q Değeri
N/A
