DocumentCode
3210004
Title
An improved PCNN model and a new removing algorithm of salt and pepper noise
Author
Wu, Yan ; Xu, Bing ; Bian, Xiao-Yue
Author_Institution
Dept. of Comput. Sci. & Technol., Tongji Univ., Shanghai, China
Volume
2
fYear
2010
fDate
13-14 Sept. 2010
Firstpage
178
Lastpage
182
Abstract
An improved PCNN model-PCNN with Positive and Negative Firing, PCNNPNF-is proposed, and also put forward a de-noising algorithm based on the time matrix of PCNNPNF. The biggest improvement is that the neuron´s output of improved PCNN has three states: positive firing, negative firing and no firing, while PCNN only has two states: firing and no firing. Experimental results show that the de-noising algorithm based on PCNNPNF can quickly find the two kinds of pulse noises, remove these noises, and reserve more information than PCNN.
Keywords
image denoising; matrix algebra; neural nets; PCNN model; PCNNPNF; denoising algorithm; negative firing; positive firing; removing algorithm; salt and pepper noise; time matrix; Computational modeling; Image segmentation; Neurons; Noise; Speech; PCNN with positive and negative firing; de-noising algorithm; pulse noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Natural Computing Proceedings (CINC), 2010 Second International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-7705-0
Type
conf
DOI
10.1109/CINC.2010.5643758
Filename
5643758
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