Cloud/shadow segmentation based on multi-level feature enhanced network for remote sensing imagery

References

• Ackerman, S. A., K. I. Strabala, W. Paul Menzel, R. A. Frey, C. C. Moeller, and L. E. Gumley. 1998. “Discriminating Clear Sky from Clouds with MODIS.” Journal of Geophysical Research: Atmospheres 103 (D24): 32141–32157. doi:10.1029/1998JD200032.
   Web of Science ®Google Scholar
• Asner, G. P. 2001. “Cloud Cover in Landsat Observations of the Brazilian Amazon.” International Journal of Remote Sensing 22 (18): 3855–3862. doi:10.1080/01431160010006926.
   Web of Science ®Google Scholar
• Chen, L.-C., G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. 2014. “Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs.” arXiv preprint arXiv:1412.7062.
   Google Scholar
• Chen, L.-C., Y. Zhu, G. Papandreou, F. Schroff, and H. Adam. 2018. “Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation.” In Proceedings of the European conference on computer vision (ECCV). Munich, Germany: Springer, 801–818.
   Google Scholar
• Dou, P., Y. Chen, and H. Yue. 2018. “Remote-Sensing Imagery Classification Using Multiple Classification Algorithm-Based AdaBoost.” International Journal of Remote Sensing 39 (3): 619–639. doi:10.1080/01431161.2017.1390276.
   Web of Science ®Google Scholar
• Gómez-Chova, L., J. Amorós, G. Camps-Valls, J. D. Martin, J. Calpe, L. Alonso, L. Guanter, J. C. Fortea, and J. Moreno. 2005. ”Cloud Detection for Chris/proba Hyperspectral Images.” In Remote Sensing of Clouds and the Atmosphere X. Vol. 5979, 59791Q. Bruges, Belgium: International Society for Optics and Photonics.
   Google Scholar
• Hanchao, L., P. Xiong, A. Jie, and L. Wang. 2018. ”Pyramid Attention Network for Semantic Segmentation.” arXiv preprint arXiv:1805.10180.
   Google Scholar
• Hou, S., W. Sun, and X. Zheng. 2014. “Overview of Cloud Detection Methods in Remote Sensing Images.” Space Electronic Technology 11 (3): 68–76.
   Google Scholar
• Jing, S., J. Huang, F. Qiang, P. Minnis, G. Jinming, and B. Jianrong 2008. “Estimation of Asian Dust Aerosol Effect on Cloud Radiation Forcing Using Fu-Liou Radiative Model and CERES Measurements.” Atmospheric Chemistry and Physics 8 (10): 2763–2771. doi:10.5194/acp-8-2763-2008.
   Web of Science ®Google Scholar
• Jun, F., J. Liu, H. Tian, L. Yong, Y. Bao, Z. Fang, and L. Hanqing 2019. “Dual Attention Network for Scene Segmentation.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Long Beach, CA, 3146–3154.
   Google Scholar
• Kaiming, H., X. Zhang, S. Ren, and J. Sun. 2016. “Deep Residual Learning for Image Recognition.” In Proceedings of the IEEE conference on computer vision and pattern recognition. Las Vegas, Nevada, USA, 770–778.
   Google Scholar
• King, M. D., W. P. M. Steven Platnick, S. A. Ackerman, and P. A. Hubanks. 2013. “Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites.” IEEE Transactions on Geoscience and Remote Sensing 51 (7): 3826–3852. doi:10.1109/TGRS.2012.2227333.
   Web of Science ®Google Scholar
• Long, J., E. Shelhamer, and T. Darrell. 2015. “Fully Convolutional Networks for Semantic Segmentation.” In Proceedings of the IEEE conference on computer vision and pattern recognition. Boston, Massachusetts, USA, 3431–3440.
   Google Scholar
• Nan, M., S. Liu, S. Qinghua, Y. Zhenjun, and X. Liu. 2019. “Cloud Detection Based on Deep Learning Combining Muti-Feature for Remote Sensing Images.” In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium , 1438–1441. Yokohama, Japan: IEEE.
   Google Scholar
• Ozkan, S., M. Efendioglu, and C. Demirpolat. 2018. “Cloud Detection from RGB Color Remote Sensing Images with Deep Pyramid Networks.” In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium , 6939–6942. Valencia, Spain: IEEE.
   Google Scholar
• Park, H., L. Lowe Sjösund, Y. Yoo, J. Bang, and N. Kwak. 2019. “Extremec3net: Extreme Lightweight Portrait Segmentation Networks Using Advanced C3-Modules.” arXiv preprint arXiv:1908.03093.
   Google Scholar
• Pengfei, L., L. Dong, H. Xiao, and X. Mingliang 2015. “A Cloud Image Detection Method Based on SVM Vector Machine.” Neurocomputing 169: 34–42. doi:10.1016/j.neucom.2014.09.102.
   Web of Science ®Google Scholar
• Qu, Y., M. Xia, and Y. Zhang. 2021. “Strip Pooling Channel Spatial Attention Network for the Segmentation of Cloud and Cloud Shadow.” Computers & Geosciences 157: 104940. doi:10.1016/j.cageo.2021.104940.
   Web of Science ®Google Scholar
• Segal-Rozenhaimer, M., L. Alan, K. Das, and V. Chirayath. 2020. “Cloud Detection Algorithm for Multi-Modal Satellite Imagery Using Convolutional Neural-Networks (CNN).” Remote Sensing of Environment 237: 111446. doi:10.1016/j.rse.2019.111446.
   Web of Science ®Google Scholar
• Shao, Z., Y. Pan, C. Diao, and J. Cai. 2019. “Cloud Detection in Remote Sensing Images Based on Multiscale Features-Convolutional Neural Network.” IEEE Transactions on Geoscience and Remote Sensing 57 (6): 4062–4076. doi:10.1109/TGRS.2018.2889677.
   Web of Science ®Google Scholar
• Shi, M., F. Xie, Z. Yue, and J. Yin. 2016. “Cloud Detection of Remote Sensing Images by Deep Learning.” In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) , 701–704. Beijing, China: IEEE.
   Google Scholar
• Simonyan, K., A. Zisserman, and A. Zisserman 2014. ”Learning Local Feature Descriptors Using Convex Optimisation.” IEEE Transactions on Pattern Analysis and Machine Intelligence 36 (8): 1573–1585 . arXiv preprint arXiv:1409.1556. doi:10.1109/TPAMI.2014.2301163.
   PubMed Web of Science ®Google Scholar
• Song, L., M. Xia, J. Jin, M. Qian, and Y. Zhang. 2021. “Suacdnet: Attentional Change Detection Network Based on Siamese U-Shaped Structure.” International Journal of Applied Earth Observation and Geoinformation 105: 102597. doi:10.1016/j.jag.2021.102597.
   Web of Science ®Google Scholar
• Surya, S.R. and P. Simon. 2013. “Automatic Cloud Detection Using Spectral Rationing and Fuzzy Clustering.” In 2013 2nd International Conference on Advanced Computing, Networking and Security , 90–95. Mangalore, India: IEEE.
   Google Scholar
• Szegedy, C., W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich. 2015. “Going Deeper with Convolutions.” In Proceedings of the IEEE conference on computer vision and pattern recognition Boston, Massachusetts, USA, 1–9.
   Google Scholar
• Tianyi, W., S. Tang, R. Zhang, J. Cao, and Y. Zhang. 2020. “Cgnet: A Light-Weight Context Guided Network for Semantic Segmentation.” IEEE Transactions on Image Processing 30: 1169–1179. doi:10.1109/TIP.2020.3042065.
   PubMed Web of Science ®Google Scholar
• Wieland, M., Y. Li, and S. Martinis. 2019. “Multi-Sensor Cloud and Cloud Shadow Segmentation with a Convolutional Neural Network.” Remote Sensing of Environment 230: 111203. doi:10.1016/j.rse.2019.05.022.
   Web of Science ®Google Scholar
• Xia, M., K. Wang, W. Song, C. Chen, and L. Yaping. 2020a. ”Non-Intrusive Load Disaggregation Based on Composite Deep Long Short-Term Memory Network.” Expert Systems with Applications 160: 113669. doi:10.1016/j.eswa.2020.113669.
   Web of Science ®Google Scholar
• Xia, M., T. Wang, Y. Zhang, J. Liu, and X. Yiqing 2021. “Cloud/shadow Segmentation Based on Global Attention Feature Fusion Residual Network for Remote Sensing Imagery.” International Journal of Remote Sensing 42 (6): 2022–2045. doi:10.1080/01431161.2020.1849852.
   Web of Science ®Google Scholar
• Xia, M., X. Zhang, L. Weng, and X. Yiqing. 2020b. ”Multi-Stage Feature Constraints Learning for Age Estimation.” IEEE Transactions on Information Forensics and Security 15: 2417–2428. doi:10.1109/TIFS.2020.2969552.
   Web of Science ®Google Scholar
• Xinhai, Y., F. Xiong, L. Jianfeng, H. Zhao, and J. Zhou. 2019. “M 2-Net: A Multi-Scale Multi-Level Feature Enhanced Network for Object Detection in Optical Remote Sensing Images.” In 2020 Digital Image Computing: Techniques and Applications (DICTA), 1–8. IEEE.
   Google Scholar
• Yu, C., C. Gao, J. Wang, Y. Gang, C. Shen, and N. Sang. 2020. “BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation.” arXiv preprint arXiv:2004.02147.
   Google Scholar
• Yuan, K., G. Meng, D. Cheng, J. Bai, S. Xiang, and C. Pan. 2017. “Efficient Cloud Detection in Remote Sensing Images Using Edge-Aware Segmentation Network and Easy-to-Hard Training Strategy.” In 2017 IEEE International Conference on Image Processing (ICIP) , 61–65. Beijing, China: IEEE.
   Google Scholar
• Zhang, X., T. Wang, G. Chen, X. Tan, and K. Zhu. 2019. “Convective Clouds Extraction from Himawari–8 Satellite Images Based on Double-Stream Fully Convolutional Networks.” IEEE Geoscience and Remote Sensing Letters 17 (4): 553–557. doi:10.1109/LGRS.2019.2926402.
   Web of Science ®Google Scholar
• Zhao, H., J. Shi, Q. Xiaojuan, X. Wang, and J. Jia. 2017. “Pyramid Scene Parsing Network.” In Proceedings of the IEEE conference on computer vision and pattern recognition Honolulu, Hawaii, USA, 2881–2890.
   Google Scholar
• Zhao, Q., T. Sheng, Y. Wang, Z. Tang, Y. Chen, L. Cai, and H. Ling. 2019. “M2det: A Single-Shot Object Detector Based on Multi-Level Feature Pyramid Network.” In Proceedings of the AAAI conference on artificial intelligence Honolulu, Hawaii, USA, Vol. 33, 9259–9266.
   Google Scholar
• Zhu, Z. and C. E. Woodcock. 2012. “Object-Based Cloud and Cloud Shadow Detection in Landsat Imagery.” Remote Sensing of Environment 118: 83–94. doi:10.1016/j.rse.2011.10.028.
   Web of Science ®Google Scholar
• Zhu, Z. and C. E. Woodcock. 2014. “Automated Cloud, Cloud Shadow, and Snow Detection in Multitemporal Landsat Data: An Algorithm Designed Specifically for Monitoring Land Cover Change.” Remote Sensing of Environment 152: 217–234. doi:10.1016/j.rse.2014.06.012.
   Web of Science ®Google Scholar