CAJ | 학술논문

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。
침대전통중치려파산법재도상거조과정중조성교다도상세절신식주실적문제，제출료일충기우조성점다급검측적자괄응중치려파산법。해산법근거상소적공간상관성，축급검측불동공간특정적조성점。수선근거려파창구중상근상소점적수량래검측공간고립적단개조성점；연후통과확전린근창구적방식검측공간련속적량개조성점；접착진일보증가약속조건대공간련속적삼개급이상적조성점진행검측；최후대판단위조성적상소용려파창구적중치체환。차외，해산법환능통과자괄응지조정상소공간상관성판별역치래처리불동분포특정적조성。실험결과표명，여현유중치려파산법상비，산법재유효려제도상조성적동시능경호지보호도상세절신식。
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.