太阳成8722(中国)有限公司-GREEN NO.1

标题：Recovering Quantitative Remote Sensing Products Contaminated by Thick Clouds and Shadows Using Multitemporal Dictionary Learning作者：Li, Xinghua; Shen, Huanfeng; Zhang, Liangpei; Zhang, Hongyan; Yuan,

Qiangqiang; Yang, Gang

来源出版物：IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 卷：52 期：11 页：7086-7098 DOI：10.1109/TGRS.2014.2307354 出版年：NOV 2014

摘要：With regard to quantitative remote sensing products in the visible and infrared ranges, thick clouds and accompanying shadows are an inevitable source of noise. Due to the absence of adequate supporting information from the data themselves, it is a formidable challenge to accurately restore the surficial information underlying large-scale clouds. In this paper, dictionary learning is expanded into the multitemporal recovery of quantitative data contaminated by thick clouds and shadows. This paper proposes two multitemporal dictionary learning algorithms, expanding on their KSVD and Bayesian counterparts. In order to make better use of the temporal correlations, the expanded KSVD algorithm seeks an optimized temporal path, and the expanded Bayesian method adaptively weights the temporal correlations. In the experiments, the proposed algorithms are applied to a reflectance product and a land surface temperature product, and the respective advantages of the two algorithms are investigated. The results show that, from both the qualitative visual effect and the quantitative objective evaluation, the proposed methods are effective.

入藏号：WOS:000340278800026

文献类型：Article

语种：English

作者关键词：Compressed sensing (CS), dictionary learning, land surface temperature (LST), multitemporal, quantitative remote sensing (QRS) product, reflectance, shadows, thick clouds

扩展关键词：ORTHOGONAL MATCHING PURSUIT; AVHRR NDVI DATA; SIGNAL RECOVERY; TIME-SERIES; HARMONIC-ANALYSIS; SENSED IMAGES; FUSED LASSO; SPARSE; RECONSTRUCTION; ALGORITHM

通讯作者地址：Li, Xinghua; Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址：lixinghua5540@whu.edu.cn; shenhf@whu.edu.cn; zlp62@whu.edu.cn; zhanghongyan@whu.edu.cn; qqyuan@sgg.whu.edu.cn; love64080@163.com

地址：

[Li, Xinghua; Shen, Huanfeng; Yang, Gang]Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Zhang, Liangpei; Zhang, Hongyan] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China.

[Yuan, Qiangqiang] Wuhan Univ, Sch Geodesy & Geomat, Wuhan 430079, Peoples R China.

研究方向：Geochemistry & Geophysics; Engineering; Remote Sensing; Imaging Science & Photographic Technology

ISSN：0196-2892