基于加权检测的脉冲噪声新滤波器

在分析噪声检测与噪声滤波原理的基础上，提出了用于恢复被脉冲噪声污染的图像的去噪算法。该算法基于方向差异性将检测窗口分解为四个子窗口，并取子窗口的中间像素与相邻像素的灰度值之差的加权平均值与预先定义的阈值进行比较，较准确地区分噪声点和信号点；然后根据方向相关依赖性，采用一种边缘保持滤波方法来重构被噪声污染像素的灰度值。实验结果证明，该算法在提高图像信噪比的同时，可以更好地保持图像的细节信息。

New impulse noise filter based on weighted detection

Based on the analysis of the principles of noise detection and noise filtering, an effective image denoising algorithm was proposed to restore images corrupted by impulse noise. The proposed algorithm utilized the directional difference to decompose the window into four subwindows, and then accurately distinguished noise points from signal points by comparing the absolute weighted mean value of the differences between the center pixel and its neighboring pixels in four subwindows with a predefined threshold. According to the directional correlation-dependence, the proposed algorithm adopted an edge-preservation filtering method to reconstruct the value of the corrupted pixel. The experimental results demonstrate that the proposed algorithm can obtain higher Peak Signal-to-Noise Ratio (PSNR) value and preserve more detailed information.