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Object-Based Area-to-Point Regression Kriging for Pansharpening

文献类型：期刊论文

作者Zhang, Yihang3; Atkinson, Peter M.1; Ling, Feng3; Foody, Giles M.2; Wang, Qunming4; Ge, Yong5; Li, Xiaodong3; Du, Yun3
刊名IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
出版日期2021-10-01
卷号59期号:10页码:8599-8614
ISSN号0196-2892
关键词Downscaling geostatistics image fusion object-based pansharpening segmentation
DOI10.1109/TGRS.2020.3041724
通讯作者Ling, Feng(lingf@whigg.ac.cn)
英文摘要Optical earth observation satellite sensors often provide a coarse spatial resolution (CR) multispectral (MS) image together with a fine spatial resolution (FR) panchromatic (PAN) image. Pansharpening is a technique applied to such satellite sensor images to generate an FR MS image by injecting spatial detail taken from the FR PAN image while simultaneously preserving the spectral information of MS image. Pansharpening methods are mostly applied on a per-pixel basis and use the PAN image to extract spatial detail. However, many land cover objects in FR satellite sensor images are not illustrated as independent pixels, but as many spatially aggregated pixels that contain important semantic information. In this article, an object-based pansharpening approach, termed object-based area-to-point regression kriging (OATPRK), is proposed. OATPRK aims to fuse the MS and PAN images at the object-based scale and, thus, takes advantage of both the unified spectral information within the CR MS images and the spatial detail of the FR PAN image. OATPRK is composed of three stages: image segmentation, object-based regression, and residual downscaling. Three data sets acquired from IKONOS and Worldview-2 and 11 benchmark pansharpening algorithms were used to provide a comprehensive assessment of the proposed OATPRK approach. In both the synthetic and real experiments, OATPRK produced the most superior pan-sharpened results in terms of visual and quantitative assessment. OATPRK is a new conceptual method that advances the pixel-level geostatistical pansharpening approach to the object level and provides more accurate pan-sharpened MS images.
WOS关键词REMOTE-SENSING DATA ; IMAGE FUSION ; SPATIAL-RESOLUTION ; MODIS IMAGES ; LANDSAT-TM ; CLASSIFICATION ; SEGMENTATION ; INFORMATION ; MULTIRESOLUTION ; ALGORITHMS
资助项目Key Research Program of Frontier Sciences, Chinese Academy of Sciences[ZDBS-LY-DQC034] ; National Natural Science Foundation of China[41801292] ; National Natural Science Foundation of China[41971297] ; Hubei Provincial Natural Science Foundation for Innovation Groups[2019CFA019] ; Natural Science Foundation of Hubei Province[2018CFB274] ; Hubei Province Natural Science Fund for Distinguished Young Scholars[2018CFA062]
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000698968700044
资助机构Key Research Program of Frontier Sciences, Chinese Academy of Sciences ; National Natural Science Foundation of China ; Hubei Provincial Natural Science Foundation for Innovation Groups ; Natural Science Foundation of Hubei Province ; Hubei Province Natural Science Fund for Distinguished Young Scholars
源URL[http://ir.igsnrr.ac.cn/handle/311030/165909]  
专题中国科学院地理科学与资源研究所
通讯作者Ling, Feng
作者单位1.Univ Lancaster, Fac Sci & Technol, Lancaster Environm Ctr, Lancaster LA1 4YQ, England
2.Univ Nottingham, Sch Geog, Nottingham NG7 2RD, England
3.Chinese Acad Sci, Innovat Acad Precis Measurement Sci & Technol, Key Lab Monitoring & Estimate Environm & Disaster, Wuhan 430077, Peoples R China
4.Tongji Univ, Coll Surveying & Geoinformat, Shanghai 200092, Peoples R China
5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Yihang,Atkinson, Peter M.,Ling, Feng,et al. Object-Based Area-to-Point Regression Kriging for Pansharpening[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2021,59(10):8599-8614.
APA Zhang, Yihang.,Atkinson, Peter M..,Ling, Feng.,Foody, Giles M..,Wang, Qunming.,...&Du, Yun.(2021).Object-Based Area-to-Point Regression Kriging for Pansharpening.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,59(10),8599-8614.
MLA Zhang, Yihang,et al."Object-Based Area-to-Point Regression Kriging for Pansharpening".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 59.10(2021):8599-8614.

入库方式： OAI收割

来源：地理科学与资源研究所

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