针对传统中值滤波算法在图像去噪过程中造成较多图像细节信息丢失的问题，提出了一种基于噪声点多级检测的自适应中值滤波算法。该算法根据像素的空间相关性，逐级检测不同空间特征的噪声点。首先根据滤波窗口中相近像素点的数量来检测空间孤立的单个噪声点；然后通过扩展邻近窗口的方式检测空间连续的两个噪声点；接着进一步增加约束条件对空间连续的三个及以上的噪声点进行检测；最后对判断为噪声的像素用滤波窗口的中值替换。此外，该算法还能通过自适应地调整像素空间相关性判别阈值来处理不同分布特征的噪声。实验结果表明，与现有中值滤波算法相比，算法在有效滤除图像噪声的同时能更好地保护图像细节信息。%To reduce the loss of image details caused by traditional median filter, an adaptive median filter algorithm is proposed based on multi-stage noise detection. According to the spatial correlation of pixels, the proposed algorithm detected the types of noise progressively. First, it detected the single noise pixel by counting the number of pixels that had similar values in filter window. Then it extended the filter window in adjacent space to detect the two pixels noise, and added constraints to detect the three or above adjacent pixels noise. Finally, the noise pixel was replaced with the median. In addition, the proposed algorithm can adjust the threshold of pixel spatial correlation discrimination adaptively to meet the processing of different distribution noises. Compared with other median filters, experimental results show that the proposed algorithm can remove noises effectively with maintaining the detail information of the original image.
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