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Offset Tracking Algorithm Based On Feature Points And Its Applications

Posted on:2021-02-17Degree:MasterType:Thesis
Country:ChinaCandidate:L C PengFull Text:PDF
GTID:2518306470463594Subject:Surveying the science and technology
Abstract/Summary:PDF Full Text Request
Interferometric Synthetic Aperture Radar(In SAR)combines Synthetic Aperture Radar(SAR)imaging technology and interferometric measurement technology.It has outstanding advantages such as wide coverage,short revisit period,high accuracy,and freedom from cloud layer in surface deformation monitoring and digital elevation model acquisition.The coregistration of SAR image is one of the key links of In SAR data processing.Accurate coregistration is very important for improving the quality of In SAR data processing.In addition,the offset obtained from registration can be directly applied to earth surface deformation research,that is,offset tracking(OT).However,the standard offset tracking is to estimate the deformation of the tie points uniformly distributed on the two SAR images,and it does not consider the scattering characteristics of the earth surface,which results in low registration efficiency and unreliable results.In order to overcome the defects of the standard offset tracking method,this paper proposes a feature point offset tracking method(FPOT).The method combines Speeded Up Robust Feature(SURF)operator,external land cover information,cross-correlation algorithm,quadtree filtering,etc.Experimental results show that this method can significantly improve the efficiency,accuracy and reliability of registration and offset tracking.The main research work of this paper is as follows:(1)It mainly explains the registration method of In SAR image and the basic flow of registration.(2)Focus on the basic principles and processing flow of offset tracking.The standard offset tracking method and processing flow are introduced,and the FPOT method is proposed to overcome the limitations of standard offset tracking.FPOT mainly includes the detection of feature points using the SURF operator,and then using external data to remove inappropriate feature points,cross-correlation processing of the remaining feature points,polynomial fitting and quadtree filtering of the obtained offsets,Finally,three-dimensional modeling is performed to obtain surface deformation.(3)Perform experimental verification.The performance of the proposed method is verified by three earthquakes in New Zealand,Nepal and Chile.The results show that the FPOT method can improve the spatial resolution of the traditional offset tracking method and has higher reliability and computational efficiency.
Keywords/Search Tags:cross-correlation, Offset tracking, Speeded Up Robust Feature, Feature Points, quadtree filtering
PDF Full Text Request
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