Dergiler / Uluslararası Mühendislik Araştırma ve Geliştirme Dergisi / 2019 / Cilt: 11 - Sayı: 2
Adaptive Right Median Filter for Salt-and-Pepper Noise Removal
- Sayfa
- 542–550
- DOI
- —
Özet
In 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.
Abstract
In 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.