Adaptive Right Median Filter for Salt-and-Pepper Noise Removal

Year 2019, Volume: 11 Issue: 2, 542 - 550, 30.06.2019

Uğur Erkan , Levent Gökrem , Serdar Enginoğlu

https://doi.org/10.29137/umagd.495904

Cited By: 5

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.

Keywords

Image denoising, Noise removal, Nonlinear filters

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