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Pattern Recognition and Image Analysis

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01-06-2022 | SELECTED PAPERS OF PRIP-21

Shadow Detection on Urban Satellite Images Based on Building Texture

Authors: Shiping Ye, Alexander Nedzved, Chaoxiang Chen, Huafeng Chen, Aliaksandr Leunikau, Alexei Belotserkovsky

Published in: Pattern Recognition and Image Analysis | Issue 2/2022

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Abstract

Shadow detection is a fundamental and complex problem in the field of computer vision and image processing. Increasing computing power has allowed many deep-learning approaches to be used to solve this problem. In this article, we consider a DSDNet neural network for shadow detection based on texture analysis of a shaded area and a bright area of an urban environment.

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X. Hu, C.-W. Fu, L. Zhu, J. Qin, and P.-A. Heng, “Direction-aware spatial context features for shadow detection and removal,” IEEE Trans. Pattern Analysis Mach. Intell. 42, 2795–2808 (2019). https://doi.org/10.1109/TPAMI.2019.2919616CrossRef

V. Nguyen, T. F. Y. Vicente, M. Zhao, M. Hoai, and D. Samaras, “Shadow detection with conditional generative adversarial networks,” in IEEE Int. Conf. on Computer Vision, Venice, 2017 (IEEE, 2017), pp. 4510–4518. https://doi.org/10.1109/ICCV.2017.483

T. F. Y. Vicente, M. Hoai, and D. Samaras, “Noisy label recovery for shadow detection in unfamiliar domains,” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Las Vegas, 2016 (IEEE, 2016), pp. 3783–3792. https://doi.org/10.1109/CVPR.2016.411

T. F. Y. Vicente, L. Hou, C.-P. Yu, M. Hoai, and D. Samaras, “Large-scale training of shadow detectors with noisily-annotated shadow examples,” in Computer Vision–ECCV 2016, Ed. by B. Leibe, J. Matas, N. Sebe, and M. Welling, Lecture Notes in Computer Science, vol. 9910 (Springer, Cham, 2016), pp. 816–832. https://doi.org/10.1007/978-3-319-46466-4_49CrossRef

J. Wang, X. Li, and J. Yang, “Stacked conditional generative adversarial networks for jointly learning shadow detection and shadow removal,” in IEEE/CVF Conf. on Computer Vision and Pattern Recognition, Salt Lake City, Utah, 2018 (IEEE, 2018), pp. 1788–1797. https://doi.org/10.1109/CVPR.2018.00192

Q. Zheng, X. Qiao, Y. Cao, and R. W. H. Lau, “Distraction Aware Shadow Detection,” in IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), Long Beach, Calif., 2019 (IEEE, 2019), pp. 5162–5171. https://doi.org/10.1109/CVPR.2019.00531

L. Zhu, Z. Deng, X. Hu, C.-W. Fu, X. Xu, J. Qin, and P.-A. Heng, “Bidirectional feature pyramid network with recurrent attention residual modules for shadow detection,” in Computer Vision–ECCV 2018, Ed. by V. Ferrari, M. Hebert, C. Sminchisescu, and Y. Weiss, Lecture Notes in Computer Science, vol. 11210 (Springer, Cham, 2018), pp. 122–137. https://doi.org/10.1007/978-3-030-01231-1_8CrossRef

J. Zhu, K. G. Samuel, S. Z. Masood, and M. F. Tappen, “Learning to recognize shadows in monochromatic natural images,” in IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, San Francisco, 2010 (IEEE, 2010), pp. 223–230. https://doi.org/10.1109/CVPR.2010.5540209

Title: Shadow Detection on Urban Satellite Images Based on Building Texture
Authors: Shiping Ye
Alexander Nedzved
Chaoxiang Chen
Huafeng Chen
Aliaksandr Leunikau
Alexei Belotserkovsky
Publication date: 01-06-2022
Publisher: Pleiades Publishing
Published in: Pattern Recognition and Image Analysis / Issue 2/2022
Print ISSN: 1054-6618
Electronic ISSN: 1555-6212
DOI: https://doi.org/10.1134/S1054661822020225

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