Multiscale DEM generation on basis of singular value decomposition

Caixian Zhang; Junli He; Wenguang Hou

doi:10.1117/12.2537903

14 February 2020 Multiscale DEM generation on basis of singular value decomposition

Caixian Zhang, Junli He, Wenguang Hou

Proceedings Volume 11432, MIPPR 2019: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 1143207 (2020) https://doi.org/10.1117/12.2537903
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China

Abstract

As the fundamental data about the terrains, DEM plays an important role in many fields. The high resolution DEM is increasingly popular. Yet, the multiscale resolution DEMs are still desired for some applications due to the fact that the low resolution DEM can reduce the memory demands with limited computational complexity. Then, how to obtain the multiscale DEMs remains an open question, which demands that the different resolution DEMs should discard the detailed information with maintaining the main information of the high resolution DEM. Moreover, the multiscale DEMs should not cost many memories. Generally, there is a contradiction. As such, this paper proposes a multiscale DEM generation method based on Singular Value Decomposition (SVD) which can establish multiscale DEMs maintaining the different details with a small quantity of memory increasement. The method is simple but effective. Lots of experiment shows its effectiveness.

Citation Download Citation

Caixian Zhang, Junli He, and Wenguang Hou "Multiscale DEM generation on basis of singular value decomposition", Proc. SPIE 11432, MIPPR 2019: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 1143207 (14 February 2020); https://doi.org/10.1117/12.2537903

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