摘要
Attenuating the noises plays an essential role in the image processing. Almost all the traditional median filters concern the removal of impulse noise having a single layer, whose noise gray level value is constant. In this paper, a new adaptive median filter is proposed to handle those images corrupted not only by single layer noise. The adaptive threshold median filter （ATMF） has been developed by combining the adaptive median filter （AMF） and two dynamic thresholds. Because of the dynamic threshold being used, the ATMF is able to balance the removal of the multiple-impulse noise and the quality of image. Comparison of the proposed method with traditional median filters is provided. Some visual examples are given to demonstrate the performance of the proposed filter.
Attenuating the noises plays an essential role in the image processing. Almost all the traditional median filters concern the removal of impulse noise having a single layer, whose noise gray level value is constant. In this paper, a new adaptive median filter is proposed to handle those images corrupted not only by single layer noise. The adaptive threshold median filter （ATMF） has been developed by combining the adaptive median filter （AMF） and two dynamic thresholds. Because of the dynamic threshold being used, the ATMF is able to balance the removal of the multiple-impulse noise and the quality of image. Comparison of the proposed method with traditional median filters is provided. Some visual examples are given to demonstrate the performance of the proposed filter.
作者简介
JIANG Bo （姜波） was born in Sichuan, China, 1981. He received the B.S. degree from Chegndu University of Technology （CDUT） in 2004. He is currently pursuing his M.S. degree in the School of Communication and Information Engineering, University of Electronic Science and Technology of China （UESTC）. His research interests include image processing and pattern recognition. HUANG Wei （黄炜） was born in Beijingo China, 1952. He received the B.S. and M.S. degrees both from UESTC in 1981 and 1984, respectively. He is currently an associate professor with UESTC. His research interests include signal processing in modern communication, audio and visual signal processing.
