DocumentCode
2113851
Title
A New Kind of Hybrid Filter Based on the ICM and the Improved Peak-and-Valley Filter
Author
Zhang Xiang-guang, Zhang
Author_Institution
Inst. of Inf., Qingdao Univ. of Sci. & Technol., Qingdao
fYear
2008
fDate
18-18 Dec. 2008
Firstpage
187
Lastpage
190
Abstract
Intersecting cortical model (ICM) has gained widely research as a new artificial neural network. It derives directly from the studies of the small mammal´s visual cortex. The improved peak-and-valley filter can keep the details of image sufficiently if the density of noise is low enough. But the image that is badly contaminated with noise, the effect of the improved peak-and-valley filter is inadequate. To overcome this shortage, this paper suggests a kind of designing project of the hybrid filter that applies the ideas of the ICM and the improved peak-and-valley filter. The theory analysis and the simulation experiments of the image processing indicate that this kind of filter can not only remove noise effectively but also keep the details of the image sufficiently.
Keywords
image denoising; median filters; neural nets; ICM; artificial neural network; hybrid filter; image noise removal; intersecting cortical model; median filter; nonlinear filter; peak-and-valley filter; Adaptive filters; Algorithm design and analysis; Analytical models; Brain modeling; Image analysis; Image processing; Information filtering; Information filters; Neural networks; Nonlinear filters; Peak-and-Valley filter; high-frequency detail; intersecting cortical model; median filter; nonlinear filter;
fLanguage
English
Publisher
ieee
Conference_Titel
Future BioMedical Information Engineering, 2008. FBIE '08. International Seminar on
Conference_Location
Wuhan, Hubei
Print_ISBN
978-0-7695-3561-6
Type
conf
DOI
10.1109/FBIE.2008.45
Filename
5076715
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