Paper
4 August 2009 Two-dimensional motion estimation algorithm based on correlation speed measurement for satellite remote sensing images
Lin Hu, Qing-hui Li, Cheng-kang Yao
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Abstract
To carry out sophisticated image motion compensation, the real-time computing problems of two-dimensional highprecision motion speed must be solved. The computation is even greater in the processing of large-size satellite remote sensing images. In order to find out the motion speed of the satellite more accurately and rapidly, a motion estimation algorithm is present in this paper. The entire pixel motion estimation is completed by line matching method accurately in the first step. In the following step, a surface fitting method is utilized to obtain the high-precision sub-pixel displacements. As the time intervals between the two or more images which are taken by the satellite detectors are known, the real-time motion speed of the satellite could be easily gotten in the end. There are two major contributions in the paper. Firstly, the line template and line matching are summed up. Therefore, the computations and searches in correlation matching processing could be reduced greatly while the efficiency is improved. Secondly, by the reasonable use of the mathematical surface fitting method, high-precision sub-pixel displacements of images could be obtained successfully. Theory analysis and experiments show that the method is reasonable and efficient.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lin Hu, Qing-hui Li, and Cheng-kang Yao "Two-dimensional motion estimation algorithm based on correlation speed measurement for satellite remote sensing images", Proc. SPIE 7383, International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications, 73833D (4 August 2009); https://doi.org/10.1117/12.834571
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KEYWORDS
Satellites

Satellite imaging

Remote sensing

Motion estimation

Earth observing sensors

Correlation function

Detection and tracking algorithms

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