Geometric correction of linear push-broom hyperspectral camera side-scan imaging

Wang Shumin; Zhang Aiwu; Hu Shaoxing; Sun Weidong; Meng Xiangang; Zhao Wenji

The side-scan imaging of the linear push-broom hyperspectral camera could solve the problem that the remote sensing images collected from the satellite platform could not get the spectral data of building facades. The main components and the key technical specifications of linear push-broom hyperspectral remote sensing system integrated and developed by our research team were stated in this paper. According to the feature of side-scan imaging, the geometric correction model was derivated in detail, which was suitable to the linear camera side-scan imaging. The methods of geo-referenced image divided into grids and spectral resampling were presented, and the solution for data loss in the collection process was also proposed. The validity and robustness of linear image distortion correction algorithm were verified through amounts of simulation experiments. It provided reference for the application of similar products.

1. Key Laboratory of 3D Information Acquisition and Application,Ministry of Education,Capital Normal University,Beijing 100048,China;

2. College of Mechanical Engineering and Automation,Beijing University of Aeronautics and Astronautics,Beijing 100083,China;

3. Department of Electronic Engineering,Tsinghua University,Beijing 100084,China

Received Date: 2013-06-10

Rev Recd Date: 2013-07-25

Publish Date: 2014-02-25

Key words:

Abstract: The side-scan imaging of the linear push-broom hyperspectral camera could solve the problem that the remote sensing images collected from the satellite platform could not get the spectral data of building facades. The main components and the key technical specifications of linear push-broom hyperspectral remote sensing system integrated and developed by our research team were stated in this paper. According to the feature of side-scan imaging, the geometric correction model was derivated in detail, which was suitable to the linear camera side-scan imaging. The methods of geo-referenced image divided into grids and spectral resampling were presented, and the solution for data loss in the collection process was also proposed. The validity and robustness of linear image distortion correction algorithm were verified through amounts of simulation experiments. It provided reference for the application of similar products.

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Reference (29)

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Geometric correction of linear push-broom hyperspectral camera side-scan imaging

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