Study on Application of Scale Invariant Feature Transform Algorithm on Automated Geometric Correction of Remote Sensing Images - Computer and Computing Technologies in Agriculture VI - Part II Access content directly
Conference Papers Year : 2013

Study on Application of Scale Invariant Feature Transform Algorithm on Automated Geometric Correction of Remote Sensing Images

Abstract

In recent years, data collected from remote sensing satellite and aerophotography have been showing a geometric sequence increase. A method of Scale Invariant Feature Transform (SIFT) algorithm could be employed for the automatic geometric fine correction. This method could avoid the impact of the rotation and zooming of template matching during the image matching process, and it can also save the labor during the image processing operation. Based on the SIFT algorithm, this paper proposes a two-step method, which firstly conducts coarse match on feature points, and then further conducts fine correction on the coarsely matched feature points by using the least squares technique. The result indicates that, this method is an effective automatic matching method for remote sensing images.
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hal-01348251 , version 1 (22-07-2016)

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Hui Deng, Limin Wang, Jia Liu, Dandan Li, Zhongxin Chen, et al.. Study on Application of Scale Invariant Feature Transform Algorithm on Automated Geometric Correction of Remote Sensing Images. 6th Computer and Computing Technologies in Agriculture (CCTA), Oct 2012, Zhangjiajie, China. pp.352-358, ⟨10.1007/978-3-642-36137-1_41⟩. ⟨hal-01348251⟩
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