Paper
11 June 2003 Multisensor image correction technique using selected variables and biased estimation model
Lianfa Bai, Weixian Qian, Yi Zhang, Baomin Zhang
Author Affiliations +
Proceedings Volume 4898, Image Processing and Pattern Recognition in Remote Sensing; (2003) https://doi.org/10.1117/12.467883
Event: Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2002, Hangzhou, China
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.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lianfa Bai, Weixian Qian, Yi Zhang, and Baomin Zhang "Multisensor image correction technique using selected variables and biased estimation model", Proc. SPIE 4898, Image Processing and Pattern Recognition in Remote Sensing, (11 June 2003); https://doi.org/10.1117/12.467883
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KEYWORDS
Calibration

Distortion

Image processing

Pattern recognition

Remote sensing

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