标题：Sparse-based reconstruction of missing information in remote sensing images from spectral/temporal complementary information作者：Li, Xinghua; Shen, Huanfeng; Zhang, Liangpei; Li, Huifang
来源出版物：ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 卷：106 页：1-15 DOI：10.1016/j.isprsjprs.2015.03.009 出版年：AUG 2015
摘要：Because of sensor failure and poor observation conditions, remote sensing (RS) images are easily subjected to information loss, which hinders our effective analysis of the earth. As a result, it is of great importance to reconstruct the missing information (MI) of RS images. Recent studies have demonstrated that sparse representation based methods are suitable to fill large-area MI. Therefore, in this paper, we investigate the MI reconstruction of RS images in the framework of sparse representation. Overall, in terms of recovering the MI, this paper makes three major contributions: (1) we propose an analysis model for reconstructing the MI in RS images; (2) we propose to utilize both the spectral and temporal information; and (3) on this basis, we make a detailed comparison of the two kinds of sparse representation models (synthesis model and analysis model). In addition, experiments were conducted to compare the sparse representation methods with the other state-of-the-art methods.
入藏号：WOS:000358699800001
文献类型：Article
语种：English
作者关键词：Analysis model, Missing information (MI), Remote sensing (RS), Sparse representation, Spectral and temporal information, Synthesis model
扩展关键词：SENSED IMAGES; TIME-SERIES; AQUA MODIS; FUSED LASSO; K-SVD; MODEL; DICTIONARIES; REGRESSION; ALGORITHM; REPRESENTATIONS
通讯作者地址：Shen, Huanfeng; Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Hubei Province, Peoples R China.
电子邮件地址：shenhf@whu.edu.cn
地址：
[Li, Xinghua; Shen, Huanfeng; Li, Huifang] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Hubei Province, Peoples R China.
[Shen, Huanfeng; Zhang, Liangpei] Wuhan Univ, Collaborat Innovat Ctr Geospatial Informat Techno, Wuhan 430072, Hubei Province, Peoples R China.
[Zhang, Liangpei] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Hubei Province, Peoples R China.
研究方向：Physical Geography; Geology; Remote Sensing; Imaging Science & Photographic Technology
ISSN：0924-2716
eISSN：1872-8235
影响因子（2014）：3.132
