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Journal of Mountain Science

, Volume 10, Issue 5, pp 790–800 | Cite as

SAR image coregistration using fringe definition detection

  • Ying-hui Yang
  • Qiang ChenEmail author
  • Guo-xiang Liu
  • Zhi-lin Li
  • Hai-qin Cheng
  • Li-yao Liu
Article

Abstract

In order to overcome the limitation of cross correlation coregistration method for Synthetic Aperture Radar (SAR) interferometric pairs with low coherence, a new image coregistration algorithm based on Fringe Definition Detection (FDD) is presented in this paper. The Fourier transformation was utilized to obtain spectrum characteristics of interferometric fringes. The ratio between spectrum mean and peak was proposed as the evaluation index for identifying homologous pixels from interferometric images. The satellites ERS-1/2 C-band SAR acquisitions covering the Yangtze River plain delta, eastern China and ALOS/PALSAR L-band images over the Longmen Shan mountainous area, southwestern China were respectively employed in the experiment to validate the proposed coregistration method. The testing results suggested that the derived Digital Elevation Model (DEM) from FDD method had good agreement with that from the cross correlation method as well as the reference DEM at high coherence area. However, The FDD method achieved a totally improved topographic mapping accuracy by 24 percent in comparison to the cross correlation method. The FDD method also showed better robustness and achieved relatively higher performance for SAR image coregistration in mountainous areas with low coherence.

Keywords

SAR image coregistration Spectrum characteristics Fringe definition detection Interferometric Synthetic Aperture Radar (InSAR) Accuracy assessment 

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References

  1. Aguera F, Fernando JA, Aguilar MA (2008) Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses. ISPRS Journal of Photogrammetry & Remote Sensing 63: 635–646. DOI: 10.1016/j.isprsjprs.2008.03.003CrossRefGoogle Scholar
  2. Barla G, Antolini F, Barla M, et al. (2010). Monitoring of the Beauregard landslide (Aosta valley, Italy) using advance and coventional techniques. Engineering Geology, 116, 218–235. DOI: 10.1016/j.enggeo.2010.09.004CrossRefGoogle Scholar
  3. Bürgmann R, Rosen PA, Fielding EJ (2000) Synthetic aperture radar interferometry to measure earth’s surface topography and its deformation. Annual review of earth and planetary sciences 28:169–209. DOI: 10.1146 /annurev.earth.28.1.169.CrossRefGoogle Scholar
  4. Castellano G, Bonilha L, Li LM, et al. (2004) Texture analysis of medical images. Clinical Radiology 59: 1061–1069. DOI: 10.1016/j.crad. 2004.07.008CrossRefGoogle Scholar
  5. Catani F, Farina P, Moretti, S, et al. (2005). On the application of SAR interferometry to geomorphological studies: Estimation of landform attributes and mass movements. Geomorphology 66: 119–131. DOI: 10.1016/j.geomorph.2004.08.012CrossRefGoogle Scholar
  6. Chen CW, Zebker HA (2002) Phase Unwrapping for Large SAR Interferograms: Statistical Segmentation and Generalized Network Models. IEEE Transactions on Geoscience and Remote Sensing 40(8): 1709–1719. DOI: 10.1109/TGRS.2002.802453CrossRefGoogle Scholar
  7. Chen Q, Liu GX, Li YS (2006) Comparison and evaluation on accuracy in satellite InSAR DEM derived using coarse and precise orbit data. Journal of remote sensing 10(4): 475–481. (In Chinese with English abstract)Google Scholar
  8. Chen Q, Liu GX, Ding XL, et al. (2010) Tight integration of GPS observations and persistent scatterer InSAR for detecting vertical ground motion in Hong Kong. International Journal of Applied Earth Observation and Geoinformation 12: 477–486. DOI: 10.1016/j.jag.2010.05.002CrossRefGoogle Scholar
  9. Ding XL, Liu GX, Li ZW, et al. (2004) Ground subsidence monitoring in Hong Kong with satellite SAR interferometry. Photogrammetry Engineering & Remote Sensing 70(10): 1151–1156.Google Scholar
  10. Gabriel AK, Goldstein RM (1988). Crossed orbit interferometry: Theory and experimental results from SIR-B. International Journal of Remote Sensing 9(5): 857–872. DOI: 10.1080/01431168808954901CrossRefGoogle Scholar
  11. Gonzalez RC, Woods RE (2003) Digital image processing Second Edition. Publishing House of Electronics Industry.Google Scholar
  12. Kampes BM, Hanssen RF, Perski Z (2003) Radar Interferometry with Public Domain Tools. Proc. FRINGE 2003 Workshop, December 1–5, Frascati, Italy.Google Scholar
  13. Li FK, Goldstein RM (1990) Studies of multibaseline spaceborne interferometric synthetic aperture radars. IEEE Transactions on Geoscience and Remote Sensing 28(1): 88–97. DOI: 10.1109/36.45749CrossRefGoogle Scholar
  14. Li N, Liu XM (2009) The characteristics analysis of image directionality in spatial domain and frequency domain. Computer and Information Technology 17(4): 22–24. (In Chinese with English abstract)Google Scholar
  15. Li ZX, Bethel James (2008) Image coregistration in SAR interferometry. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVII: 433–438.Google Scholar
  16. Liu GX, Ding XL, Li ZL, et al. (2001) Co-Registration of Satellite SAR Complex Images. Acta Geodaetica et Cartographica Sinica 30(1): 60–65. (In Chinese with English abstract)Google Scholar
  17. Martens G, Poppe C, Lambert P, et al. (2010) Noise- and compression-robust biological features for texture classification. IEEE Transactions on Visualization and Computer Graphics: 915–922. DOI: 10.1007/s00371-010-0455-9Google Scholar
  18. Nitti DO, Hanssen RF, Reficec A (2008) Evaluation of DEM-assisted SAR coregistration. Image and Signal Processing for Remote Sensing 7109(XIV): 1–14. DOI: 10.1117/12.802767Google Scholar
  19. Scharroo R, Visser P (1998) Precise orbit determination and gravity field improvement for the ERS satellites. Journal of Geophysical Research 103(C4): 8113–8127. DOI: 10.1029/97JC03179CrossRefGoogle Scholar
  20. Scheiber Rolf, Moreira Alberto (2000) Coregistration of interferometric SAR Images using spectral diversity. IEEE transaction on Geoscience and remote sensing 38(5): 2179–2190. DOI: 10.1109/36.868876CrossRefGoogle Scholar
  21. Selva Jesús, Juan M, Sanchez Lopez (2007) Efficient Interpolation of SAR images for coregistration in SAR interferometry. IEEE Geoscience and remote sensing letters 4(3): 411–415. DOI: 10.1109/LGRS.2007.895961CrossRefGoogle Scholar
  22. Singhroy V, Couture R, Molch K, et al (2006). InSAR Monitoring of post-Landslide activity. Proceedings, Geoscience and Remote Sensing Symposium, IGARSS, IEEE International Conference, 1635–1638. DOI: 10.1109/IGARSS.2006.422Google Scholar
  23. Zebker HA, Goldstein RM (1986) Topographic mapping from interferometric synthetic aperture radar observation. Journal of Geophysical research 91: 4993–4999. DOI: 10.1029/JB091iB05p04993CrossRefGoogle Scholar
  24. Zeng QM, Xie XT (2004) A FFT-based complex correlation function method applied to interferometric complex image corregistration. Acta Geodaetica et Cartographica Sinica 33(2): 127–131. (In Chinese with English abstract).Google Scholar
  25. Zhao CY, Lu Z, Zhang Q, et al. (2012) Large-area landslide detection and monitoring with ALOS/PALSAR imagery data over Northern California and Southern Oregon, USA. Remote Sensing of Environment 124: 348–359. DOI: 10.16/j.rse.2012.05.025CrossRefGoogle Scholar

Copyright information

© Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ying-hui Yang
    • 1
  • Qiang Chen
    • 1
    Email author
  • Guo-xiang Liu
    • 1
  • Zhi-lin Li
    • 1
  • Hai-qin Cheng
    • 1
    • 2
  • Li-yao Liu
    • 1
  1. 1.Department of Remote Sensing and Geoinformation EngineeringSouthwest Jiaotong UniversityChengduChina
  2. 2.School of Civil Engineering and ArchitectureEast China Jiaotong UniversityNanchangChina

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