دانلود رایگان مقاله انگلیسی رویکرد فازی سازگار نوع 2 برای فیلتر نویز نمک و فلفل در تصاویر سیاه سفید - IEEE 2018

Abstract

This paper proposes a novel adaptive Type-2 fuzzy filter for removing salt and pepper noise from the images. The filter removes noise in two steps. In the first step, the pixels are categorized as good or bad based on their primary membership function (MF) values in the respective filter window. In this paper, two approaches have been proposed for finding threshold between good or bad pixels by designing primary MFs. a) MFs with distinct Means and same Variance and b) MFs with distinct Means and distinct Variances. The primary MFs of the Type-2 fuzzy set is chosen as Gaussian membership functions (GMFs). Whereas, in the second step, the pixels categorized as bad are denoised. For denoising, a novel Type-1 fuzzy approach based on a weighted mean of good pixels is presented in the paper. The proposed filter is validated for several standard images with the noise level as low as 20% to as high as 99%. The results show that the proposed filter performs better in terms of peak signal-noise-ratio (PSNR) values compared to other state-of-theart algorithms.

V. CONCLUSION

This paper proposes a novel adaptive Type-2 fuzzy filter for removing SAP noise from grayscale images. The use of either of the two proposed approaches in first step of fuzzy filter detects noisy pixels in the filter window. In the subsequent step, the proposed weighted mean Type-1 fuzzy approach denoises bad pixels in the respective filter window. The proposed approach is validated on several grayscale images. The experimental results show that proposed filter outperforms other state-of-the-art algorithms. Moreover, the filter preserves meaningful image details even at noise level as high as 99%.