摘要
提出一种针对椒盐噪声的SVC多窗口图像去噪方法。利用局部统计特性将像素点标记为信号点、可能的正噪声点及可能的负噪声点。在后两类中根据灰度值不同迭代使用支持向量聚类确定出噪声点的位置,并对其进行多窗口滤波。实验证明该方法在噪声率达到70%以上时具有很好的去噪效果,尤其在保持图像细节方面效果显著。
The paper presents an image denoising method based on Support Vector Clustering（SVC） aiming at salt and pepper noise.The pixel point is marked as signal,the points of possible positive noise and the points of possible negative noise using local statistical characteristics.In the latter two categories,authors use iterating SVC on the gray value of pixels and deal it with noise filtering.Thus,the position of the noise will be located and the noise will be handled.Experiments show that the method presented in this paper has a very good effect on image denoising achieving 70% ,especially has the better effect on the detail preserving.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第36期195-197,共3页
Computer Engineering and Applications
基金
湖南省自然科学基金(No.06JJ50109)~~
关键词
支持向量聚类
图像去噪
椒盐噪声
Support Vector Clustering（SVC）
image denoising
salt and pepper noise
