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Remote Sensing Letters Volume 12, 2021 - Issue 4
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Research Article

Generating a highly detailed DSM from a single high-resolution satellite image and an SRTM elevation model

Hamed Amini AmirkolaeeSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, IranCorrespondence[email protected]
&
Hossein ArefiSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, IranORCID Iconhttps://orcid.org/0000-0002-8014-624X
ORCID Icon
Pages 335-344 | Received 06 Nov 2020, Accepted 11 Jan 2021, Published online: 23 Feb 2021

References

  • Amini Amirkolaee, H., and H. Arefi. 2019. “CNN-based Estimation of Pre-and Post-earthquake Height Models from Single Optical Images for Identification of Collapsed Buildings.” Remote Sensing Letters 10 (7): 679–688. doi:10.1080/2150704X.2019.1601277.
  • Amirkolaee, H. A., and H. Arefi. 2019a. “Convolutional Neural Network Architecture for Digital Surface Model Estimation from Single Remote Sensing Image.” Journal of Applied Remote Sensing 13 (1): 016522. doi:10.1117/1.JRS.13.016522.
  • Amirkolaee, H. A., and H. Arefi. 2019b. “Height Estimation from Single Aerial Images Using a Deep Convolutional Encoder-decoder Network.” ISPRS Journal of Photogrammetry and Remote Sensing 149: 50–66. doi:10.1016/j.isprsjprs.2019.01.013.
  • Ghamisi, P., and N. Yokoya. 2018. “Img2dsm: Height Simulation from Single Imagery Using Conditional Generative Adversarial Net.” IEEE Geoscience and Remote Sensing Letters 15 (5): 794–798. doi:10.1109/LGRS.2018.2806945.
  • Hoffman, J. 2019. “Cramnet: Layer-wise Deep Neural Network Compression with Knowledge Transfer from a Teacher Network.” arXiv preprint arXiv:1904.05982.
  • Li, X., M. Wang, and Y. Fang. 2020. “Height Estimation from Single Aerial Images Using a Deep Ordinal Regression Network.” arXiv preprint arXiv:2006.02801.
  • Liu, C.-J., V. A. Krylov, P. Kane, G. Kavanagh, and R. Dahyot. 2020. “IM2ELEVATION: Building Height Estimation from Single-View Aerial Imagery.” Remote Sensing 12 (17): 2719. doi:10.3390/rs12172719.
  • Lo, C.-F., Z.-S. CHEN, C.-R. KO, and C.-Y. Wu. 2020. “Methods and Systems for Automatic Object Detection from Aerial Imagery.” Google Patents.
  • Mou, L., and X. X. Zhu. 2018. “IM2HEIGHT: Height Estimation from Single Monocular Imagery via Fully Residual Convolutional-deconvolutional Network.” arXiv preprint arXiv:1802.10249.
  • Nayar, S. K., and Y. Nakagawa. 1994. “Shape from Focus.” IEEE Transactions on Pattern Analysis and Machine Intelligence 16 (8): 824–831. doi:10.1109/34.308479.
  • Rottensteiner, F., and C. Briese. 2003. “Automatic Generation of Building Models from LIDAR Data and the Integration of Aerial Images.”
  • Sinz, F. H., J. Q. Candela, G. H. Bakır, C. E. Rasmussen, and M. O. Franz. 2004. “Learning Depth from Stereo.” Paper presented at the Joint Pattern Recognition Symposium, pp. 245–252 . Springer, Berlin, Heidelberg..
  • Ullman, S. 1979. “The Interpretation of Structure from Motion.” Proceedings of the Royal Society of London. Series B. Biological Sciences 203 (1153): 405–426.
  • Vedaldi, A., and K. Lenc. 2015. “Matconvnet: Convolutional Neural Networks for Matlab.” Paper presented at the Proceedings of the 23rd ACM international conference on Multimedia, Brisbane, Australia.
  • Yu, F., and V. Koltun. 2015. “Multi-scale Context Aggregation by Dilated Convolutions.” arXiv preprint arXiv:1511.07122.
  • Zhang, Z., J. Huang, T. Jiang, B. Sui, and X. Pan. 2020. “Semantic Segmentation of Very High-resolution Remote Sensing Image Based on Multiple Band Combinations and Patchwise Scene Analysis.” Journal of Applied Remote Sensing 14 (1): 016502. doi:10.1117/1.JRS.14.016502.

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