Gaussian noise filter based on PCNN

Author

Yi-de, Ma ; Fei, Shi ; Lian, Li

Author_Institution

Sch. of Inf. Sci. & Eng., Lanzhou Univ., China

Volume

1

fYear

2003

fDate

14-17 Dec. 2003

Firstpage

149

Abstract

The pulse coupled neural network (PCNN) has gained wide research as a new artificial neural network. It was derived directly from the study of the small mammal´s visual cortex. PCNN is a model with multiple parameters, and finding the proper values of these parameters is an onerous task. So a simplified PCNN is put forward and its performance in removing Gaussian noise of image is discussed in this article. The algorithm of PCNN combined with median filter and the step-by-step modifying algorithm, which is also based on PCNN, are proposed, and the experiment results of the two algorithms are analyzed and compared with that of the median filter and the Wiener filter.

Keywords

Gaussian noise; Wiener filters; image denoising; median filters; neural nets; Gaussian noise filter; Wiener filter; artificial neural network; image noise; mammal visual cortex; median filter; noise removal; pulse coupled neural network; step-by-step modifying algorithm; Artificial neural networks; Brain modeling; Degradation; Gaussian noise; Image processing; Image segmentation; Neurons; Nonlinear filters; Smoothing methods; Wiener filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on

Conference_Location

Nanjing

Print_ISBN

0-7803-7702-8

Type

conf

DOI

10.1109/ICNNSP.2003.1279233

Filename

1279233