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A fully automatic registration approach based on contour and SIFT for HJ-1 images 被引量:5

A fully automatic registration approach based on contour and SIFT for HJ-1 images
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摘要 To achieve a fully automatic registration between HJ-1 CCD images and HJ-1 infrared images is a difficult task as it must deal with the varying illuminations and resolutions of the images,different perspectives,and the local deformations within the images.In this paper,aimed at those registration issues,a fully automatic registration approach based on contour and SIFT is proposed.The registration technique performs a pre-registration process using contour feature matching algorithm that decides the overlapping region between a reference image and an input image.Once the coarse regions are obtained,it performs a fine registration process based on SIFT detector and a local adaptive matching strategy.In the fine registration process,image blocking theory is used,which not only speeds up the features extraction and matching,but also makes the matching point pairs distributed uniformly in images,and further improves the accuracy of input image rectification.Experiments with visible images and infrared images from HJ-1A/B demonstrate the efficiency and the accuracy of the proposed technique for multisource remote sensing images registration. To achieve a fully automatic registration between HJ-1 CCD images and HJ-1 infrared images is a difficult task as it must deal with the varying illuminations and resolutions of the images, different perspectives, and the local deformations within the images. In this paper, aimed at those registration issues, a fully automatic registration approach based on contour and SIFT is proposed. The registration technique performs a pre-registration process using contour feature matching algorithm that decides the overlapping region between a reference image and an input image. Once the coarse regions are obtained, it performs a fine registration process based on SIFT detector and a local adaptive matching strategy. In the fine registration process, image blocking theory is used, which not only speeds up the features extraction and matching, but also makes the matching point pairs distributed uniformly in images, and further improves the accuracy of input image rectification. Experiments with visible images and infrared images from HJ-1A/B demonstrate the efficiency and the accuracy of the proposed technique for multi- source remote sensing images registration.
出处 《Science China Earth Sciences》 SCIE EI CAS 2012年第10期1679-1687,共9页 中国科学(地球科学英文版)
基金 supported by National Basic Research Program of China(Grant No. 2007CB714404)
关键词 automatic registration CONTOUR SIFT coarse matching fine registration local adaptive strategy 红外图像 全自动化 SIFT 注册 基础 轮廓 特征匹配 CCD图像
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  • 1CHEN Wei1,2,CAO ChunXiang1,HE QiSheng1,2,GUO HuaDong3,ZHANG Hao1,2,LI RenQiang4,ZHENG Sheng1,2,XU Min1,2,GAO MengXu1,2,ZHAO Jian1,2,LI Sha1,NI XiLiang1,2,JIA HuiCong1,JI Wei1,TIAN Rong1,2,LIU Cheng1,2,ZHAO YuXing5 & LI JingLu6 1 State Key Laboratory of Remote Sensing Science,Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University,Beijing 100101,China,2 Graduate University of Chinese Academy of Sciences,Beijing 100049,China,3 Center for Earth Observation and Digital Earth,Chinese Academy of Sciences,Beijing 100190,China,4 China Key Laboratory of Ecological Network Observation and Modeling,Institute of Geographical Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China,5 Ordos Forestry Sand Control Science Institute,Dongsheng 017000,China,6 Inner Mongolia Biomass Thermoelectricity Limited Company,Wushen 017300,China.Quantitative estimation of the shrub canopy LAI from atmosphere-corrected HJ-1 CCD data in Mu Us Sandland[J].Science China Earth Sciences,2010,53(S1):26-33. 被引量:6
  • 2YANG Jun1,GONG Peng2,ZHOU JinXing3,HUANG HuaBing2 & WANG Lei2 1 Key Laboratory of Silviculture and Conservation,Ministry of Education,Beijing Forestry University,Beijing 100083,China,2 State Key Laboratory of Remote Sensing Science,jointly sponsored by the Institute of Remote Sensing Applications,Chinese Academy of Sciences and Beijing Normal University,Beijing 100101,China,3 Institute of Desertification Studies,Chinese Academy of Forestry,Beijing 100091,China.Detection of the urban heat island in Beijing using HJ-1B satellite imagery[J].Science China Earth Sciences,2010,53(S1):67-73. 被引量:9
  • 3WANG Qiao1,WU ChuanQing1,LI Qing1 & LI JunSheng2 1 Satellite Environment Center,Ministry of Environmental Protection,Beijing 100029,China,2 Center for Earth Observation and Digital Earth,Chinese Academy of Sciences,Beijing 100190,China.Chinese HJ-1A/B satellites and data characteristics[J].Science China Earth Sciences,2010,53(S1):51-57. 被引量:18
  • 4SUN Lin1,2,SUN ChangKui1,LIU QinHuo2 & ZHONG Bo2 1Geomatics College,Shandong University of Science and Technology,Qingdao 266510,China,2State Key Laboratory of Remote Sensing Science,Chinese Academy of Sciences,Beijing 100101,China.Aerosol optical depth retrieval by HJ-1/CCD supported by MODIS surface reflectance data[J].Science China Earth Sciences,2010,53(S1):74-80. 被引量:14
  • 5GUO ZhiFeng1,CHI Hong1,2 & SUN GuoQing1,3 1State Key Laboratory of Remote Sensing Science,Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University,Institute of Remote Sensing Applications,Chinese Academy of Sciences,Beijing 100101,China,2Graduate University of Chinese Academy of Sciences,Beijing 100049,China,3Department of Geography University of Maryland,College Park,MD 20742,USA.Estimating forest aboveground biomass using HJ-1 Satellite CCD and ICESat GLAS waveform data[J].Science China Earth Sciences,2010,53(S1):16-25. 被引量:21
  • 6朱海涌.环境与灾害监测预报小卫星数据应用评价[J].干旱环境监测,2010,24(1):39-42. 被引量:3

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同被引文献34

  • 1李晓明,郑链,胡占义.基于SIFT特征的遥感影像自动配准[J].遥感学报,2006,10(6):885-892. 被引量:154
  • 2孙卜郊,周东华.基于NCC的快速匹配算法[J].传感器与微系统,2007,26(9):104-106. 被引量:29
  • 3Zaunick E, Levenhagen J, Janschek K. GEO Satellite Image Navigation with Cloud Detection Using Multispectral Payload Image Data[C]//Proc. of IFAC Workshop on Aerospace Guidance, Navigation and Flight Control Systems. Sanara, Russia: [s. n.], 2009: 7-12.
  • 4Gibbs B. Goes Image Navigation and Registration[J]. SatMagazine, 2008, 7(1): 32-42.
  • 5Madani H, Carr J L, Schoeser C. Image Registration Using Auto Landmark[C]//Proc. of 2004.
  • 6IEEE International Geoscience and Remote Sensing Symposium. Anchorage, USA: [s. n.], 2004: 107-108.
  • 7NOAA. Earth Location User's Guide(ELUG)[EB/OL]. (2005- 07-29). http://www.osd.noaa.gov/GVAR_Downloads/documents/ Earth Location_Users_Guide.pdf.
  • 8Carr J, Madani H. Measuring Image Navigation and Registra- tion Performance at the 3- Level Using Platinum Quality Landmarks[C]//Proc. of the 20th International Symposium on Space Flight Dynamics. Washington D. C., USA: [s. n.], 2007: 1-12.
  • 9Eugenio F, Marquesr F. Automatic Satellite Image Georef- erencing Using a Contour-matching Approach[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(12): 2869-2880.
  • 10Ackerrnann J. Navigation of Polar Orbiter Imager Data with Landmarks[EB/OL]. (2002-10-10). http://www.eumetsat.int/ groups/ops/documents/document/pdf_tm I 0_eps_landmarks-na v.pdf.

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