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Proceedings Paper

Motion-blur parameter estimation of remote sensing image based on quantum neural network
Author(s): Kun Gao; Xiao-xian Li; Yan Zhang; Ying-hui Liu
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Paper Abstract

During optical remote sensing imaging procedure, the relative motion between the sensor and the target may corrupt image quality seriously. The precondition of restoring the degraded image is to estimate point spread function (PSF) of the imaging system as precisely as possible. Because of the complexity of the degradation process, the transfer function of the degraded system is often completely or partly unclear, which makes it quite difficult to identify the analytic model of PSF precisely. Inspired by the similarity between the quantum process and imaging process in the probability and statistics fields, one reformed multilayer quantum neural network (QNN) is proposed to estimate PSF of the degraded imaging system. Different from the conventional artificial neural network (ANN), an improved quantum neuron model is used in the hidden layer instead, which introduces a 2-bit controlled NOT quantum gate to control output and 4 texture and edge features as the input vectors. The supervised back-propagation learning rule is adopted to train network based on training sets from the historical images. Test results show that this method owns excellent features of high precision, fast convergence and strong generalization ability.

Paper Details

Date Published: 29 November 2011
PDF: 11 pages
Proc. SPIE 8200, 2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 82001L (29 November 2011); doi: 10.1117/12.910623
Show Author Affiliations
Kun Gao, Key Lab. of Photoelectronic Imaging Technology and System (China)
Beijing Institute of Technology (China)
Xiao-xian Li, Key Lab. of Photoelectronic Imaging Technology and System (China)
Beijing Institute of Technology (China)
Yan Zhang, Key Lab. of Photoelectronic Imaging Technology and System (China)
Beijing Institute of Technology (China)
Ying-hui Liu, Key Lab. of Photoelectronic Imaging Technology and System (China)
Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 8200:
2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology
Toru Yoshizawa; Ping Wei; Jesse Zheng, Editor(s)

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