Automatic remote sensing imagery registration based on improved SIFT

Huawei Li; Chongguang Zhu; Fengping Di

doi:10.1117/12.774762

14 November 2007 Automatic remote sensing imagery registration based on improved SIFT

Huawei Li, Chongguang Zhu, Fengping Di

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 679037 (2007) https://doi.org/10.1117/12.774762
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

With the rapid development of remote sensing technology and the current diversity of new sensors, we can get more and more multi-source remote sensing data in the same area. It is the key to match those remote sensing data in wide application. And most current methods of registering remote sensing imagery require human involvement, so, there is a need for automated techniques in the remote sensing area. Especially the multi-source and multi-temporal remote sensing data call for new demands for automated techniques. In this paper, the authors proposed a feature matching approach based on improved SIFT (Scale Invariant Feature Transform) for remote sensing imagery registration. In this method, the feature mainly is the specific characteristic of the remote sensing imagery. The experiment results using this automatic remote sensing registration method indicate that the improved descriptors are more distinctive and robust, which results in a higher matching performance and a better matching efficiency.

Citation Download Citation

Huawei Li, Chongguang Zhu, and Fengping Di "Automatic remote sensing imagery registration based on improved SIFT", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 679037 (14 November 2007); https://doi.org/10.1117/12.774762

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KEYWORDS

Remote sensing

Image registration

Digital imaging

Sensors

Image analysis

Databases

Image enhancement

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