Comparative Analysis of Digital Elevation Model Generation Methods Based on Sparse Modeling

被引:1
作者
Fuse, Takashi [1 ]
Imose, Kazuki [2 ]
机构
[1] Univ Tokyo, Dept Civil Engn, 7-3-1 Hongo,Bunkyo Ku, Tokyo 1138656, Japan
[2] Cent Japan Railway Co, JR Tokai Shinagawa Bldg A,2-1-85 Konan,Minato Ku, Tokyo 1088204, Japan
关键词
digital elevation model (DEM) generation; aerial laser bathymetry (ALB); sparse modeling; sparse coding; compressed sensing; total variation; comparative analysis; DECOMPOSITION; RESOLUTION; SELECTION; SET;
D O I
10.3390/rs15112714
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With the spread of aerial laser bathymetry (ALB), seafloor topographies are being measured more frequently. Nevertheless, data deficiencies occur owing to seawater conditions and other factors. Conventional interpolation methods generally need to produce digital elevation models (DEMs) with sufficient accuracy. If the topographic features are considered as a basis, the DEM should be reproducible based on a combination of such features. The purpose of this study is to develop new DEM generation methods based on sparse modeling. Based on a review of the definitions of sparsity, we developed DEM generation methods based on a discrete cosine transform (DCT), DCT with elastic net, K-singular value decomposition (K-SVD), Fourier regularization, wavelet regularization, and total variation (TV) minimization, and conducted a comparative analysis. The developed methods were applied to artificially deficient DEM and ALB data, and their accuracy was evaluated. Thus, as a conclusion, we can confirm that the K-SVD method is appropriate when the percentage of deficiencies is low, and that the TV minimization method is appropriate when the percentage of deficiencies is high. Based on these results, we also developed a method integrating both methods and achieved an RMSE of 0.128 m.
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页数:19
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