School of Science, Northwestern Polytechnical University, Xi'an, 710129, China.
PLoS One. 2018 Oct 26;13(10):e0205736. doi: 10.1371/journal.pone.0205736. eCollection 2018.
In this paper, a two-stage filter for removing salt-and-pepper noise using noise detector based on characteristic difference parameter and adaptive directional mean filter is proposed. The first stage firstly detects the noise corrupted pixels by combining characteristic difference parameter and gray level extreme, then develops an improved adaptive median filter to firstly restore them. The second stage introduces a restoration scheme to further restore the noise corrupted pixels, which firstly divides them into two types and then applies different restoration skills for the pixels based on the classification result. One type of pixels is restored by the mean filter and the other type of pixels is restored by the proposed adaptive directional mean filter. The new filter firstly adaptively selects the optimal filtering window and direction template, then replaces the gray level of noise corrupted pixel by the mean value of pixels on the optimal template. Experimental results show that the proposed filter outperforms many existing main filters in terms of noise suppression and detail preservation.
本文提出了一种基于特征差分参数和自适应方向均值滤波器的噪声探测器的两级滤波器，用于去除椒盐噪声。第一阶段通过结合特征差分参数和灰度极值来首先检测噪声污染像素，然后开发一种改进的自适应中值滤波器来首先对其进行恢复。第二阶段引入了一种恢复方案，进一步恢复噪声污染像素，该方案首先将它们分为两类，然后根据分类结果对像素应用不同的恢复技术。一类像素通过均值滤波器进行恢复，另一类像素通过提出的自适应方向均值滤波器进行恢复。新滤波器首先自适应地选择最佳滤波窗口和方向模板，然后用最佳模板上的像素平均值替换噪声污染像素的灰度值。实验结果表明，与许多现有的主要滤波器相比，该滤波器在噪声抑制和细节保留方面表现更好。
