吴云华
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Image Registration Based on SOFM Neural Network Clustering
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Affiliation of Author(s):航天学院

Journal:PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017)

Key Words:Image Registration Self-Organizing Feature Maps Clustering Analysis Neural Network

Abstract:Spacecraft autonomous navigation method based on remote sensing image is a novel method which has been put into practical use in recent year. However, with the restricted computation resource onboard, this method still needs to look for a better way to improve its speed to satisfy real-time requirement. According to the problem above, this paper proposed an alternate method to faster image registration progress with the combination of SURF (Speed-Up Robust Features) and SOFM (Self-Organizing Feature Map). SURF is a sophisticated algorithm which is invariant to scaling and rotation, and SOFM is a kind of neural network which is used for clustering analysis in this paper. Then, a new algorithm called Similarity-Clustering Algorithm (SCA) is presented to analysis the result of clustering. Besides, a performance index called Precision is defined to determine the best value of Epoch for SOFM neural network training. The experimental results demonstrate that the proposed approach for registration has good adaptability for real-time practical application.

ISSN No.:2161-2927

Translation or Not:no

Date of Publication:2017-01-01

Co-author:葛林林,hb,Chen Zhiming,陈林

Correspondence Author:葛林林,wyh

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Researcher

Alma Mater:哈尔滨工业大学

Education Level:哈尔滨工业大学

Degree:Doctoral Degree in Engineering

School/Department:College of Astronautics

Discipline:Guidance, Navigation, and Control

Business Address:航天学院D11-507

Contact Information:yunhuawu@nuaa.edu.cn

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