摘要
针对图像中同时存在椒盐噪声和高斯噪声,提出一种基于灰度极限和脉冲耦合神经网络(PCNN)滤除混合噪声的新方法。首先,根据灰度极值定位出椒盐噪声点;其次,在滤波窗口中对椒盐噪声点进行均值滤波;然后,利用PCNN赋时矩阵定位出高斯噪声点;最后,自适应调整可变灰度步长,选择不同滤波方法滤除高斯噪声。实验结果表明提出的算法较常见的混合噪声滤波方法在主观滤波效果和客观评价指标峰值信噪比(PSNR)及信噪比改善因子(ISNR)两方面均有明显的优势。
A new method of filtering mixed noise based on limited grayscale and Pulse Coupled Neural Network（PCNN） was proposed for an image contaminated by salt and pepper noise and Gaussian noise.First,salt and pepper noise was identified according to the limited grayscale in a detecting window.Then the noise was filtered via mean filter in a filtering window.Subsequently,Gaussian noise was identified by using the time matrix of PCNN.Finally the Gaussian noise was filtered by some different filters based on variable step.The experimental results show that the proposed method has more advantages not only in filtering effects but also in objective evaluation indexes of Peak Signal-to-Noise Ratio（PSNR） and Improved Signal-to-Noise Ratio（ISNR） compared to some traditional methods.
出处
《计算机应用》
CSCD
北大核心
2012年第3期729-731,735,共4页
journal of Computer Applications
基金
云南大学第二批中青年骨干教师基金及在职培养博士启动基金资助项目(21132014)
第三届云南大学研究生科研课题资助基金资助项目(YNUY201046)
关键词
椒盐噪声
高斯噪声
灰度极限
脉冲耦合神经网络
均值滤波
可变步长
salt and pepper noise
Gaussian noise
limited grayscale
Pulse Coupled Neural Network（PCNN）
mean filtering
variable step
