标题: A fast and robust cirrus removal method for Landsat 8/9 images

作者: Jiang, T (Jiang, Tao); Shen, HF (Shen, Huanfeng); Li, HF (Li, Huifang); Zhang, C (Zhang, Chi); Xu, LY (Xu, Liying); Lin, DK (Lin, Dekun)

来源出版物: INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION  卷: 128  文献号: 103691  DOI: 10.1016/j.jag.2024.103691  Early Access Date: FEB 2024  Published Date: 2024 APR  

摘要: High-quality cirrus removal plays a crucial role in remote sensing data analysis. Cirrus parallaxes are commonly observed within the vicinity of cirrus clouds in the visible and near-infrared (VNIR) bands of Landsat 8/9 images. Cirrus parallaxes have a nonnegligible effect on cirrus removal, but the existing methods do not account for the correction of parallaxes. Meanwhile, large-scale image processing involves intensive computation that requires extensive computing time. To address the effect of cirrus parallaxes and the low processing efficiency, we propose a fast and robust cirrus removal (FRCR) method. FRCR has achieved the first realization of the statistics law of cirrus parallax between the VNIR and cirrus bands, thus realizing the cirrus parallax correction. In addition, FRCR introduces an automatic sampling method to obtain the regression samples for practicality. Then, a Compute Unified Device Architecture (CUDA) based Newton method with constraints is introduced to parallelize the computation, to improve the computational performance. Experiment results of various scenarios demonstrate that the FRCR method can achieve high-quality cirrus removal by eliminating cirrus parallaxes, and significantly improving computational performance.

作者关键词: High-quality cirrus removal; Cirrus parallaxes; Cirrus parallax laws and correction; Automatic sampling; CUDA

地址: [Jiang, Tao; Shen, Huanfeng; Li, Huifang; Xu, Liying; Lin, Dekun] Wuhan Univ, Sch Resource & Environm Sci, Hubei Luojia Lab, Wuhan 430079, Peoples R China.

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

[Zhang, Chi] Guangzhou Urban Planning & Design Survey Res Inst, Guangzhou 510060, Peoples R China.

[Zhang, Chi] Guangdong Enterprise Key Lab Urban Sensing Monitor, Guangzhou 510060, Peoples R China.

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

Shen, HF (通讯作者)，Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan 430079, Peoples R China.

电子邮件地址: shenhf@whu.edu.cn

影响因子：7.5