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Automated accurate registration method between UAV image and Google satellite map

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Abstract

Because Unmanned Aerial Vehicle (UAV) image exhibits low positioning accuracy, the accurate registration of the image is required. Since the viewpoint direction, capturing time and shoot height are considerably different between the UAV image and google satellite map, the existing methods cannot match two images accurately. For the registration between the UAV image and google satellite map, a full-automated image registration method was proposed based on deep convolution feature. Such method consists of five steps: automatically reference images downloading, uniform key point extraction, deep convolution features computation, accurately feature matching and image registration. The reference image was downloaded from google map service according to the approximate location and region of the UAV image. The deep convolution feature was extracted using the pre-trained VGG16 model. Finally, many experiments were performed to verify the efficiency of the proposed method, and the results demonstrate that the proposed method is more effective and robust than the existing method.

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Acknowledgements

This work is supported by the transverse project & Massive image data storage platform. Grant No. is Y8620V1C01.

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Authors and Affiliations

  1. Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China

    Yijie Yuan, Wei Huang, Huaiyu Xu, Hongying Zuo & Ruidan Su

  2. University of Chinese Academy of Sciences, Beijing, China

    Yijie Yuan, Wei Huang & Huaiyu Xu

  3. Department of Computer Science and Technology, Shanghai University, Shanghai, China

    Xiangxin Wang

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  1. Yijie Yuan
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  2. Wei Huang
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  3. Xiangxin Wang
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  4. Huaiyu Xu
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  5. Hongying Zuo
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Correspondence to Hongying Zuo or Ruidan Su.

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Hongying Zuo and Ruidan Su are both corresponding authors and both contributed equally to this manuscript.

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Yuan, Y., Huang, W., Wang, X. et al. Automated accurate registration method between UAV image and Google satellite map. Multimed Tools Appl 79, 16573–16591 (2020). https://doi.org/10.1007/s11042-019-7729-7

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  • DOI: https://doi.org/10.1007/s11042-019-7729-7

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