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Self-similarity Based Multi-layer DEM Image Up-Sampling

  • Xin Zheng
  • Ziyi Chen
  • Qinzhe Han
  • Xiaodan Deng
  • Xiaoxuan Sun
  • Qian YinEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 965)

Abstract

As one of the basic data of GIS, DEM data which expresses the surface elevation data is widely used in many fields. How to obtain a wide range of high-precision elevation data is a big challenge, the simple interpolation algorithm currently used is less accurate. Due to the fractal data characteristics of terrain data, DEM data shows strong self-similarity. Based on this feature, this paper proposes a multi-layer Dem image up-sampling method. Image up-sampling is performed multiple times in layers on the low-resolution DEM image, therefore, high-precision DEM information with less error is obtained. In this paper, elevation data of 30 m is expanded to elevation data of 10 m by gradually using this method. Experimental results show that the algorithm can achieve good results and has a small deviation from the real elevation data of 10 m.

Keywords

Up-sampling DEM Self-similarity 

Notes

Acknowledgments

The research work described in this paper was fully supported by the National Key R&D program of China (2017YFC1502505) and the grant from the National Natural Science Foundation of China (61472043). Qian Yin is the author to whom all correspondence should be addressed.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Xin Zheng
    • 1
  • Ziyi Chen
    • 1
  • Qinzhe Han
    • 1
  • Xiaodan Deng
    • 1
  • Xiaoxuan Sun
    • 1
  • Qian Yin
    • 1
    Email author
  1. 1.Image Processing and Pattern Recognition Laboratory, College of Information Science and TechnologyBeijing Normal UniversityBeijingChina

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