Uğur ERKAN, Levent GÖKREM, Serdar ENGİNOĞLU

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

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.

Anahtar Kelimeler:

Image denoising, Noise removal, Nonlinear filters

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

Keywords:

Image denoising, Noise removal Nonlinear filters, Nonlinear functions, Matrix algebra,

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