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Proceedings Paper

Multisensor image correction technique using selected variables and biased estimation model
Author(s): Lianfa Bai; Weixian Qian; Yi Zhang; Baomin Zhang
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Paper Abstract

In many case, the traditional image geometric calibration method, i.e. polynomial warping will not accommodate the precision transformation required. So the least square method is often used to improve the precision. But because of the multi-relation, the calibration is not so good as expected. In this paper, the theory and experiment studies on the traditional least square method used in image calibration are carried out systematically. With regard to the diversity of image distortion, the selected variables method is applied, which smartly analyses the variables of transformation equation of different images. Through reducing the variables unnecessary, the multi-relation is reduced. Then the ridge-regression is employed, in which the biased estimation is used to solve the huge confidence interval problem that is resulted by multi-relation. The theory and experiment results show that by using this new technique, the multi-relation is reduced and the precision is improved apparently.

Paper Details

Date Published: 11 June 2003
PDF: 7 pages
Proc. SPIE 4898, Image Processing and Pattern Recognition in Remote Sensing, (11 June 2003); doi: 10.1117/12.467883
Show Author Affiliations
Lianfa Bai, Nanjing Univ. of Science and Technology (China)
Weixian Qian, Nanjing Univ. of Science and Technology (China)
Yi Zhang, Nanjing Univ. of Science and Technology (China)
Baomin Zhang, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 4898:
Image Processing and Pattern Recognition in Remote Sensing
Stephen G. Ungar; Shiyi Mao; Yoshifumi Yasuoka, Editor(s)

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