DocumentCode :
1588450
Title :
The Depth-Variant Image Restoration Based on Hopfield Neural Network
Author :
Wang, Yu ; He, Xiaohai ; Wang, Huazhang
Author_Institution :
Sichuan Univ., Chengdu
Volume :
2
fYear :
2007
Firstpage :
363
Lastpage :
366
Abstract :
In this paper we presented a full-parallel Hopfield neural network based on a new model of the three-dimensional (3D) Gaussian point spread function (PSF) to restore the microscopic optical slices. As the result of the diffraction of the microscope´s objective, the imaging model in three-dimensional optical- sectioning microscopy incorporates spherical aberration that worsens with increasing depth under the coverslip and changes in the PSF. Two- dimensional image restoration and three-dimensional serial images restoration are used to analyze the capability of the network, and the performance shows that the continuous Hopfield network can restore the blurred images of the depth-variant microscopic image.
Keywords :
Gaussian processes; Hopfield neural nets; aberrations; image restoration; optical microscopy; optical transfer function; 3D Gaussian point spread function; 3D optical-sectioning microscopy; 3D serial images restoration; depth-variant image restoration; full-parallel Hopfield neural network; microscopic optical slices restoration; spherical aberration; Biology computing; Biomedical optical imaging; Computer networks; Degradation; Fluorescence; Hopfield neural networks; Image restoration; Neural networks; Optical computing; Optical microscopy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
Type :
conf
DOI :
10.1109/ICNC.2007.716
Filename :
4344377
Link To Document :
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