控制工程 ›› 2013, Vol. 20 ›› Issue (5): 829-832.

• 综述与评论 • 上一篇    下一篇

简化型PCNN 的混合噪声图像滤波算法研究

张艳珠李媛李小娟   

  • 出版日期:2013-09-20 发布日期:2013-11-28

The Research of Hybrid Noise Filtering for Images Based on Pulse Coupled Neural Network

ZHANG Yan-zhuLI YuanLI Xiao-juan   

  • Online:2013-09-20 Published:2013-11-28

摘要:

针对脉冲噪声和高斯噪声构成混合噪声的特点,提出了一种基于简化型脉冲耦合神经网络( Pulse Coupled Neural Network,PCNN) 滤波算法,利用了简化模型的几个技术特性,适当的选取参数,并在算法中结合了形态学方法、中值滤波和维纳滤波,该算法相对于均值滤波和中值滤波算法来说具有更好的抑制混合噪声干扰的能力,能较好地保持图像的边缘和细节信息。通过大量实验证实,应用简化型PCNN 滤波算法对滤除灰度图像所受混合噪声的效果较好。在与其他算法的比较中,该算法优于传统的滤波算法,不但能有效地滤除混合噪声,并且计算量适中,具有较好的实时性,同时随着图像受混合噪声污染程度的增大,优势更加明
显。

关键词: 脉冲耦合神经网络, 混合噪声, 滤波

Abstract:

To the speciality of mixed noise constituted by pulse noise and Gauss noise,we present a comprehensive algorithm in this
text,which is based on the simplified PCNN model,utilizing several technique specialities of the model,selecting parameters properly,
and combining with mathematical morphology method,median filtering and wiener filtering. This method performs better than average
filters and median filters on hybrid noise reduction while retaining edges and detail information of the image. Experiments show that the
effect of eliminating grey image mixed noise which applying the simplified PCNN eliminating algorithm proposed in this paper is good.
This algorithm can show a big advantage when in the comparison with other algorithms. This algorithm not only can effectively filter hybrid
noise but also can excel in real-time tasks because of its reduced computation complexity. With the increase of the image populated
by blends noise,the advantage is obvious.

Key words: PCNN, hybrid noise, filtration