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林德坤(博士生)、沈焕锋的论文在IEEE GEOSCIENCE AND REMOTE SENSING LETTERS刊出
发布时间:2024-07-09     发布者:易真         审核者:任福     浏览次数:

标题: A Framework for Generating High-Resolution Seamless Remote Sensing Images for Regional-Scale Areas

作者: Lin, DK (Lin, Dekun); Shen, HF (Shen, Huanfeng); Qiu, ZH (Qiu, Zhonghang); Zhu, SC (Zhu, Shaocong); Huang, WL (Huang, Wenli); Jiang, T (Jiang, Tao)

来源出版物: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS : 21 文献号: 6010305 DOI: 10.1109/LGRS.2024.3380165 Published Date: 2024

摘要: High-resolution seamless remote sensing (HRSRS) images are essential foundational data for natural resource monitoring and land-use assessment. However, high spatial resolution (HR) Earth observation from satellites typically has a long revisit period, and optical images can be widely obscured by clouds. Furthermore, the geometry and radiation issues make the generation of HRSRS images a challenging task. In this letter, to systematically address these issues, we propose a robust and efficient framework designed to generate HRSRS images for regional-scale areas, integrating various mature image processing technologies and jointing super-resolution (SR) reconstruction and thick cloud removal for the first time. In particular, the framework can realize adaptive reconstruction of lost spatial information on demand based on the satellite observation coverage and thick cloud coverage information. The effectiveness and reliability of the framework was demonstrated by its successful application in generating a 1-m resolution quarterly seamless image of the city of Wuhan, Hubei province, China, using 34 images acquired by the Chinese Gaofen (GF)-1/2/6/7 satellites. The experimental results show that both the intermediate results and final results achieve a satisfactory visual and quantitative effect. For example, SR reconstruction improves the spatial resolution of low-resolution images from 2 to 1 m, thus increasing the spatial frequency and entropy by about 0.62 and 0.12, respectively.

作者关键词: Remote sensing; Spatial resolution; Clouds; Satellite broadcasting; Image reconstruction; Cloud computing; Radiometry; Gaofen (GF); remote sensing image; spatial seamless; super-resolution (SR); thick cloud removal

地址: [Lin, Dekun; Shen, Huanfeng; Qiu, Zhonghang; Zhu, Shaocong; Huang, Wenli; Jiang, Tao] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

通讯作者地址: Shen, HF (通讯作者)Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址: lindekun@whu.edu.cn; shenhf@whu.edu.cn; qiu_zh@whu.edu.cn; zhushaocong@whu.edu.cn; wenli.huang@whu.edu.cn; jiangta0@whu.edu.cn

影响因子:4