DocumentCode :
2113835
Title :
A New Kind of Super-Resolution Reconstruction Algorithm Based on the ICM and the Bilinear Interpolation
Author :
Zhang Xiang-guang, Zhang
Author_Institution :
Inst. of Inf., Qingdao Univ. of Sci. & Technol., Qingdao
fYear :
2008
fDate :
18-18 Dec. 2008
Firstpage :
183
Lastpage :
186
Abstract :
Super-resolution reconstruction of image is highly dependent on the data outliers. This work addresses the super-resolution reconstruction design of the Intersecting Cortical Model (ICM) algorithm applied to the bilinear interpolation. Based on a simplification of the Pulse-Coupled Neural Network (PCNN), we propose a design strategy to reduce the effects of outliers on the reconstructed image. 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 theory analysis and the simulation experiments of the image processing indicate that this kind of super-resolution reconstruction algorithm can not only reduce the effects of outliers effectively but also keep the details of the image sufficiently.
Keywords :
image reconstruction; image resolution; interpolation; neural nets; bilinear interpolation; intersecting cortical model algorithm; mammal visual cortex; pulse-coupled neural network; super-resolution image reconstruction algorithm; Algorithm design and analysis; Analytical models; Artificial neural networks; Brain modeling; Image analysis; Image processing; Image reconstruction; Image resolution; Interpolation; Reconstruction algorithms; bilinear interpolation; 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.2008.44
Filename :
5076714
Link To Document :
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