Erkan, UğurGökrem, LeventEnginoğlu, Serdar2025-01-272025-01-2720191308-5514https://doi.org/10.29137/umagd.495904https://search.trdizin.gov.tr/tr/yayin/detay/405773https://hdl.handle.net/20.500.12428/15984In image processing, nonlinear filters are commonly used as a pre-process for noise removal before applying any advanced processing such as classification and clustering to an image. The adaptive filters being a kind of the nonlinear filters mainly perform better than the others in salt-and-pepper noise. In this paper, we first define a new median method, i.e. right median (rm). We then define a new adaptive nonlinear filter developed via rm, namely Adaptive Right Median Filter (ARMF), for saltand-pepper noise removal. Afterwards, we compare the results of ARMF with some of the known filters by using 12 test images and two image quality metrics: Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM). The results show that ARMF outperforms the other methods at all the noise density except 80% and 90% in the mean percentages. Finally, we discuss the need for further research.eninfo:eu-repo/semantics/openAccessBilgisayar BilimleriYazılım MühendisliğiBilgisayar BilimleriBilgi SistemleriBilgisayar BilimleriDonanım ve MimariBilgisayar BilimleriTeori ve MetotlarArticle11254255010.29137/umagd.495904405773