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Proceedings Paper

Algorithm for the blind deconvolution of images based on neural networks
Author(s): Boxin Zuo; Jinwen Tian; Li Zu; Anhong Chen
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Paper Abstract

An iterative blind deconvolution algorithm for degrade image is presented in this paper. The algorithm includes two steps, namely, the estimation of the point spread function of degrade image and the restoration using estimated point spread function. Two different Hopfield neural networks are built for realizing the two steps. An iterative procedure is used to control the restoration process. The simulation results indicate that the method is effective for blind deconvolution with high convergence speed.

Paper Details

Date Published: 15 November 2007
PDF: 7 pages
Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 67871B (15 November 2007); doi: 10.1117/12.749379
Show Author Affiliations
Boxin Zuo, Huazhong Univ. of Science and Technology (China)
Jinwen Tian, Huazhong Univ. of Science and Technology (China)
Li Zu, China Univ. of Geology Science (China)
Anhong Chen, National Defense Key Lab. for Aerospace Intelligent Control Technology (China)

Published in SPIE Proceedings Vol. 6787:
MIPPR 2007: Multispectral Image Processing
Henri Maître; Hong Sun; Jianguo Liu; Enmin Song, Editor(s)

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