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沈焕锋的论文Recovering missing pixels for Landsat ETM...在REMOTE SENSING OF ENVIRONMENT刊出
发布时间:2013-04-08     发布者:yz         审核者:     浏览次数:

标题:Recovering missing pixels for Landsat ETM plus SLC-off imagery using multi-temporal regression analysis and a regularization method

作者:Zeng, Chao;Shen, Huanfeng;Zhang, Liangpei

来源出版物:REMOTE SENSING OF ENVIRONMENT 卷:131 页:182-194 出版年:APR 15 2013

摘要:Since the scan line corrector (SLC) of the Landsat Enhanced Thematic Mapper Plus (ETM +) sensor failed permanently in 2003, about 22% of the pixels in an SLC-off image are not scanned. To improve the usability of the ETM + SLC-off data, we propose an integrated method to recover the missing pixels. The majority of the degraded pixels are filled using multi-temporal images as referable information by building a regression model between the corresponding pixels. When the auxiliary multi-temporal data cannot completely recover the missing pixels, a non-reference regularization algorithm is used to implement the pixel filling. To assess the efficacy of the proposed method, simulated and actual SLC-off ETM + images were tested. The quantitative evaluations suggest that the proposed method can predict the missing values very accurately. The method performs especially well in edges, and is able to keep the shape of ground features. According to the assessment results of the land-cover classification and NDVI, the recovered data are also suitable for use in further remote sensing applications.

入藏号:WOS:000315546900014

文献类型:Article

语种:English

作者关键词:ETM, SLC-off, Gap filling

扩展关键词:TERM ACQUISITION PLAN; EVOLUTION; GAPS; FILL

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

电子邮件地址:shenhf@whu.edu.cn; zlp62@public.wh.hb.cn

地址:

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

[Shen, Huanfeng] WuhanUniv, Sch Resource & Environm Sci,Wuhan430079,Hubei, Peoples RChina

研究方向:Environmental Sciences & Ecology; Remote Sensing; Imaging Science & Photographic Technology

ISSN:0034-4257