Ground-based remote sensing cloud detection using dual pyramid network and encoder–decoder constraint
Zhang, Zhong and Yang, Shuzhen and Liu, Shuang and Cao, Xiaozhong and Durrani, Tariq S. (2022) Ground-based remote sensing cloud detection using dual pyramid network and encoder–decoder constraint. IEEE Transactions on Geoscience and Remote Sensing, 60. ISSN 0196-2892 (https://doi.org/10.1109/tgrs.2022.3163917)
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Abstract
Many methods for ground-based remote sensing cloud detection learn representation features using the encoder–decoder structure. However, they only consider the information from single scale, which leads to incomplete feature extraction. In this article, we propose a novel deep network named dual pyramid network (DPNet) for ground-based remote sensing cloud detection, which possesses an encoder–decoder structure with dual pyramid pooling module (DPPM). Specifically, we process the feature maps of different scales in the encoder through dual pyramid pooling. Then, we fuse the outputs of the dual pyramid pooling in the same pyramid level using the attention fusion. Furthermore, we propose the encoder–decoder constraint (EDC) to relieve information loss in the process of encoding and decoding. It constrains the values and the gradients of probability maps from the encoder and the decoder to be consistent. Since the number of cloud images in the publicly available databases for ground-based remote sensing cloud detection is limited, we release the TJNU Large-scale Cloud Detection Database (TLCDD) that is the largest database in this field. We conduct a series of experiments on TLCDD, and the experimental results verify the effectiveness of the proposed method.
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Item type: Article ID code: 81196 Dates: DateEvent29 March 2022Published29 March 2022AcceptedNotes: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Subjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 17 Jun 2022 15:05 Last modified: 11 Nov 2024 13:31 URI: https://strathprints.strath.ac.uk/id/eprint/81196