A fuzzy switching filter for removing impulse noise

Song Li, Caizhu Wang, Yequi Li, Ling Wang, S. Sakata, H. Sekiya, S. Kuroiwa
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Abstract

In recent years, fuzzy set theory has been successfully used in various applications. A typical application area for using fuzzy techniques is to restore images corrupted by impulse noise. In this paper, we present a new framework of removing impulse noise. The most important points is that the types of images are estimated by using the FINDRM and the efficient detail preserving approach (EDPA). When it is estimated that an image has many white and black pixels, the detected noise pixels from the FINDRM are re-checked by using alpha-trimmed means. Oppositely, when it is estimated that an image has a few white and black pixels, the detection results from the FINDRM are used directly. Experimental results show that the proposed algorithm provides significant improvement of PSNR compared with the conventional techniques, and the results are visually very impressive.
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一种去除脉冲噪声的模糊开关滤波器
近年来,模糊集理论已成功地应用于各种领域。模糊技术的一个典型应用领域是恢复被脉冲噪声损坏的图像。本文提出了一种去除脉冲噪声的新框架。最重要的是利用FINDRM和高效细节保留方法(EDPA)对图像类型进行估计。当估计图像有许多黑白像素时,使用alpha修剪方法重新检查FINDRM检测到的噪声像素。相反,当估计图像有少量白色和黑色像素时,直接使用FINDRM的检测结果。实验结果表明,与传统算法相比,该算法显著提高了PSNR,且效果显著。
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