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Efficient adaptive fuzzy-based switching weighted average filter for the restoration of impulse corrupted digital images

机译:高效的基于模糊的自适应开关加权平均滤波器,用于恢复脉冲损坏的数字图像

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摘要

This study proposes a new fuzzy adaptive filter for the restoration of impulse corrupted digital images. The proposed filter incorporates fuzzy functions to model the uncertainties, while detecting and correcting impulses. The traditional, SMALL fuzzy function is used to identify the non-impulsive nature of the detected corrupted pixels in the initial step. For the better restoration of detected impulsive pixels, a modified version of Gaussian function is utilised to determine the similarity among the detected uncorrupted pixels. The proposed correction scheme provides more weight to the uncorrupted pixels that show much similarity with other uncorrupted pixels in the window while replacing impulses. The proposed filter adapts to various noisy and image conditions and is capable of suppressing noise while preserving image details. The experimental results in terms of subjective and objective metrics favour the proposed algorithm than many other prominent filters in literature.
机译:这项研究提出了一种新的模糊自适应滤波器,用于恢复脉冲损坏的数字图像。所提出的滤波器结合了模糊函数来对不确定性进行建模,同时检测和校正脉冲。传统的SMALL模糊函数用于在初始步骤中识别检测到的损坏像素的非脉冲性质。为了更好地恢复检测到的脉冲像素,利用高斯函数的修改版本来确定检测到的未损坏像素之间的相似性。所提出的校正方案为未损坏的像素提供了更多的权重,这些未损坏的像素在替换脉冲时与窗口中的其他未损坏的像素表现出很大的相似性。所提出的滤波器适应各种噪声和图像条件,并且能够在保留图像细节的同时抑制噪声。在主观和客观指标方面的实验结果比文献中许多其他著名的过滤器更喜欢该算法。

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