标題: An Enhanced Double-Filter Deep Residual Neural Network for Generating Super Resolution DEMs
作者: Zhou, AN (Zhou, Annan); Chen, YM (Chen, Yumin); Wilson, JP (Wilson, John P.); Su, H (Su, Heng); Xiong, ZX (Xiong, Zhexin); Cheng, QS (Cheng, Qishan)
來源出版物: REMOTE SENSING 卷: 13 期: 16 文獻号: 3089 DOI: 10.3390/rs13163089 出版年: AUG 2021
摘要: High-resolution DEMs are important spatial data, and are used in a wide range of analyses and applications. However, the high cost to obtain high-resolution DEM data over a large area through sensors with higher precision poses a challenge for many geographic analysis applications. Inspired by the convolution neural network (CNN) excellent performance in super-resolution (SR) image analysis, this paper investigates the use of deep residual neural networks and low-resolution DEMs to generate high-resolution DEMs. An enhanced double-filter deep residual neural network (EDEM-SR) method is proposed, which uses filters with different receptive field sizes to fuse and extract features and reconstruct a more realistic high-resolution DEM. The results were compared with those generated with the bicubic, bilinear, and EDSR methods. The numerical accuracy and terrain feature preserving effects of the EDEM-SR method can generate reconstructed DEMs that better match the original DEMs, show lower MAE and RMSE, and improve the accuracy of the terrain parameters. MAE is reduced by about 30 to 50% compared with traditional interpolation methods. The results show how the EDEM-SR method can generate high-resolution DEMs using low-resolution DEMs.
入藏号: WOS:000690123400001
語言: English
文獻類型: Article
作者關鍵詞: convolutional neural networks; DEMs; super-resolution; deep learning
地址: [Zhou, Annan; Chen, Yumin; Su, Heng; Xiong, Zhexin; Cheng, Qishan] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.
[Wilson, John P.] Univ Southern Calif, Spatial Sci Inst, Los Angeles, CA 90089 USA.
通訊作者地址: Chen, YM (通訊作者),Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.
電子郵件地址: 2016301110183@whu.edu.cn; ymchen@whu.edu.cn; jpwilson@usc.edu; 2017301110076@whu.edu.cn; 2016301110034@whu.edu.cn; 2016301110176@whu.edu.cn
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