DocumentCode :
539182
Title :
Feature-based image fusion scheme for satellite recognition
Author :
Han Pan ; Gang Xiao ; Zhongliang Jing
Author_Institution :
Inst. of Aerosp. Sci. & Technol., Shanghai Jiao Tong Univ., Shanghai, China
fYear :
2010
fDate :
26-29 July 2010
Firstpage :
1
Lastpage :
6
Abstract :
Despite the variety of technologies and algorithms studied, satellite recognition is not fully researched in the uncontrolled space environments. In this paper, a low complexity and efficient satellite recognition scheme by fusing infrared and visible image features for recognition was brought forward. Invariant moments are taken to represent the characteristics of satellites´ pictures. Unlike optimal image feature fusion by classic intelligent computing algorithms, a low computation and efficient fusion rules are developed to improve the performance of recognition. Due to the compute power of space-based computer, a new fusion method by associating combined blur and affine moments invariant (CBAI) with Zernike moments is introduced. The experiments results with Semi-physical simulation images indicate that the recognition consistently demonstrated better performance than others solely based on either infrared or visible image.
Keywords :
Zernike polynomials; image fusion; CBAI; Zernike moment; affine moments invariant; blur; feature-based image fusion; infrared feature; satellite recognition; space-based computer; visible image feature; Classification algorithms; Feature extraction; Image recognition; Principal component analysis; Satellites; Support vector machine classification; PCA; combined blur and affine moment; fusion based feature; satellite recognition; zernike moments;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion (FUSION), 2010 13th Conference on
Conference_Location :
Edinburgh
Print_ISBN :
978-0-9824438-1-1
Type :
conf
DOI :
10.1109/ICIF.2010.5712006
Filename :
5712006
Link To Document :
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