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李慧芳、博士生羅爽的論文在 IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 刊出
發布時間:2021-06-30     發布者:易真         審核者:     浏覽次數:

标題: ESPFNet: An Edge-Aware Spatial Pyramid Fusion Network for Salient Shadow Detection in Aerial Remote Sensing Images

作者: Luo, S (Luo, Shuang); Li, HF (Li, Huifang); Zhu, RZ (Zhu, Ruzhao); Gong, YT (Gong, Yuting); Shen, HF (Shen, Huanfeng)

來源出版物: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING : 14 : 4633-4646 DOI: 10.1109/JSTARS.2021.3066791 出版年: 2021

摘要: Shadows can hinder image interpretation in aerial remote sensing images. The existing shadow detection methods focus on all shadow regions and detect the shadow regions directly, but they ignore the fact that salient shadows have a more significant effect. In this work, a novel edge-aware spatial pyramid fusion network (ESPFNet) under a multitask learning framework is proposed for salient shadow detection in aerial remote sensing images. ESPFNet has three components: a parallel spatial pyramid (PSP) structure; an edge detection module (EDM); and an edge-aware multibranch integration (EMI). The PSP structure is constructed to extract multiscale features from the input image and fuse them gradually. The EDM then integrates the shallow features and deep features to detect the shadow edges. Finally, the EMI incorporates the edge features with multibranch features, and then concatenates them with the shallow features to generate the salient shadow detection result. The experimental analyses confirm the effectiveness of the ESPFNet method in both the qualitative and quantitative performance, compared to the existing methods, with the F-score reaching 92.04% in the salient shadow test set.

入藏号: WOS:000652787700002

語言: English

文獻類型: Article

作者關鍵詞: Feature extraction; Image edge detection; Remote sensing; Task analysis; Electromagnetic interference; Data mining; Buildings; Aerial remote sensing images; convolutional neural network; multitask learning; salient shadow detection

地址: [Luo, Shuang; Li, Huifang; Gong, Yuting; Shen, Huanfeng] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Zhu, Ruzhao] KylinSoft Co Ltd, Changsha 410073, Peoples R China.

[Shen, Huanfeng] Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan 430079, Peoples R China.

通訊作者地址: Li, HF (通訊作者)Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

電子郵件地址: sluo@whu.edu.cn; huifangli@whu.edu.cn; zhuruzhao@kylinos.cn; yutinggong@whu.edu.cn; shenhf@whu.edu.cn

影響因子:3.827


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