摘要
针对现有中值滤波算法对于高密度噪声图像以及纹理细腻图像的边缘处理能力欠佳的缺陷,提出一种基于动态窗口的自适应中值滤波算法。该算法根据噪声点与周围信息的关联程度调整噪声点滤波值,从而更好地处理图像的细节部分。该算法中的自适应策略加强了滤波算法的去噪性能,使其对于含有任意噪声密度的图像也能很好地进行噪声滤除。通过仿真分析,新算法对于细节丰富的图像以及高密度噪声的图像滤波效果良好,有效地提高了图像的峰值信噪比,去噪效果相比其他方法更加优秀。
Aiming to solve the problem that median filtering algorithm has poor processing capacity on high-density noise image and delicate texture image,a dynamic window-based adaptive median filter algorithm was proposed.According to the associated level between noise-point information and its surrounding,the new algorithm adjusted the noise-point filter value,which can deal with the details of the images better.The adaptive strategies of the new algorithm strengthen the denoising performance of the filtering algorithm,which is good at dealing with any density noise.The simulation analysis shows that the new algorithm can effectively improve the peak signal to noise ratio of the image,and the denoising effect is more satisfactory than other methods.
出处
《计算机应用》
CSCD
北大核心
2011年第2期390-392,405,共4页
journal of Computer Applications
基金
江苏省教育厅自然科学基金资助项目(06KJB520005)
关键词
椒盐噪声
噪声检测
动态窗口
自适应策略
滤波算法
salt-and-pepper noise
noise detection
dynamic window
adaptive strategy
filter algorithm
