Improvement of the accuracy of InSAR image co-registration based on tie points - a review

Zou, Weibao and Li, Yan and Li, Zhilin and Ding, Xiaoli (2009) Improvement of the accuracy of InSAR image co-registration based on tie points - a review. Sensors, 9 (2). pp. 1259-1281. ISSN 1424-8220

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Abstract

Interferometric Synthetic Aperture Radar (InSAR) is a new measurement technology, making use of the phase information contained in the Synthetic Aperture Radar (SAR) images. InSAR has been recognized as a potential tool for the generation of digital elevation models (DEMs) and the measurement of ground surface deformations. However, many critical factors affect the quality of InSAR data and limit its applications. One of the factors is InSAR data processing, which consists of image co-registration, interferogram generation, phase unwrapping and geocoding. The co-registration of InSAR images is the first step and dramatically influences the accuracy of InSAR products. In this paper, the principle and processing procedures of InSAR techniques are reviewed. One of important factors, tie points, to be considered in the improvement of the accuracy of InSAR image co-registration are emphatically reviewed, such as interval of tie points, extraction of feature points, window size for tie point matching and the measurement for the quality of an interferogram.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
Depositing User: Dr Yan Li
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 21 Jan 2010 10:11
Last Modified: 30 Jul 2013 04:23
Uncontrolled Keywords: co-registration; InSAR; interferogram; window size; interval of tie points
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
09 Engineering > 0906 Electrical and Electronic Engineering > 090609 Signal Processing
09 Engineering > 0906 Electrical and Electronic Engineering > 090699 Electrical and Electronic Engineering not elsewhere classified
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Identification Number or DOI: doi: 10.3390/s90201259
URI: http://eprints.usq.edu.au/id/eprint/6644

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