Volume 34 Issue 4
Apr.  2009
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CHENG Liang, GONG Jianya, HAN Peng, SONG Xiaogang. Automatic Optimization for Affine Invariant Feature Matching on Remote Sensing Imagery[J]. Geomatics and Information Science of Wuhan University, 2009, 34(4): 418-422.
Citation: CHENG Liang, GONG Jianya, HAN Peng, SONG Xiaogang. Automatic Optimization for Affine Invariant Feature Matching on Remote Sensing Imagery[J]. Geomatics and Information Science of Wuhan University, 2009, 34(4): 418-422.
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Automatic Optimization for Affine Invariant Feature Matching on Remote Sensing Imagery

  • 1Department of Geographic Information Science,Nanjing University,22 Hankou Road,Nanjing 210093,China;2State Key Laboratory for Information Engineering in Surveying,Mapping and Remote Sensing, Wuhan University,Wuhan 430079,China;3Xi'an Institute of Surveying and Mapping,1 Middle Yanta Road,Xi'an 710054,China;4State Key Laboratory of Earthquake Dynamics,Institute of Geology,China Earthquake Administration, Qijiahuozi,Beijing 100029,China

Funds: 国家973计划资助项目(2006CB701300)；国家教育部高等学校博士学科点专项科研基金(20070284001)
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  • Received Date: January 19, 2009
  • Revised Date: January 19, 2009
  • Published Date: April 04, 2009
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    • Abstract
  • An automated optimization method for affine invariant feature matching on remote sensing imagery is proposed.The correct matching rate is developed as an evaluation criterion of the optimized processing for affine invariant feature matching,which guarantees the quality of the optimized processing and realizes automated processing.Overlap rate is calculated by projecting a local region onto the corresponding region based on homograhpy,upon which a correct matching rate is determined.For different purposes,two classical optimization solutions are introduced.The algorithm for each solution is implemented based on the proposed method.By using one stereo satellite image and two stereo aerial images with different types,the experiment indicates that the results of feature matching can be optimized automated and accurately by our method according to corresponding optimization solution.
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