Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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Change detection algorithm based on amplitude statistical distribution for high resolution SAR image

통계분포에 기반한 고해상도 SAR 영상의 변화탐지 알고리즘 구현 및 적용

  • Lee, Kiwoong (Department of Avionics, Korea Aerospace University) ;
  • Kang, Seoli (Department of Avionics, Korea Aerospace University) ;
  • Kim, Ahleum (Department of Avionics, Korea Aerospace University) ;
  • Song, Kyungmin (Department of Avionics, Korea Aerospace University) ;
  • Lee, Wookyung (Department of Avionics, Korea Aerospace University)
  • 이기웅 (한국항공대학교 항공전자공학과) ;
  • 강서리 (한국항공대학교 항공전자공학과) ;
  • 김아름 (한국항공대학교 항공전자공학과) ;
  • 송경민 (한국항공대학교 항공전자공학과) ;
  • 이우경 (한국항공대학교 항공전자공학과)
  • Received : 2015.04.30
  • Accepted : 2015.06.17
  • Published : 2015.06.30
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Abstract

Synthetic Aperture Radar is able to provide images of wide coverage in day, night, and all-weather conditions. Recently, as the SAR image resolution improves up to the sub-meter level, their applications are rapidly expanding accordingly. Especially there is a growing interest in the use of geographic information of high resolution SAR images and the change detection will be one of the most important technique for their applications. In this paper, an automatic threshold tracking and change detection algorithm is proposed applicable to high-resolution SAR images. To detect changes within SAR image, a reference image is generated using log-ratio operator and its amplitude distribution is estimated through K-S test. Assuming SAR image has a non-gaussian amplitude distribution, a generalized thresholding technique is applied using Kittler and Illingworth minimum-error estimation. Also, MoLC parametric estimation method is adopted to improve the algorithm performance on rough ground target. The implemented algorithm is tested and verified on the simulated SAR raw data. Then, it is applied to the spaceborne high-resolution SAR images taken by Cosmo-Skymed and KOMPSAT-5 and the performances are analyzed and compared.

최근 위성 Synthetic Aperture Radar (SAR) 영상의 해상도가 개선됨에 따라 이에 대한 수요가 증가할 것으로 보이며 향후 새로운 응용시장으로 성장할 것으로 예측되고 있다. 특히, 화산이나 지진과 같은 자연 재해에 대한 예측이나 지형의 미세한 변화를 탐지하기 위한 용도로 SAR 영상의 활용도가 증가하고 있다. 기존의 변화탐지 알고리즘을 고해상도 SAR 영상에 적용할 경우, 영상간의 기하학적 구조, 스펙클의 영향 등으로 변화탐지 정확도가 저하될 수 있다. 또한, SAR 영상의 경우 지형적 특성에 따라 영상의 통계적 분포가 다르므로 영상의 통계분포를 반영한 임계값 추정이 필요하다. 본 연구에서는 고해상도 SAR 영상의 통계적 분포특성을 반영하여 임계값을 이용하는 변화탐지 알고리즘을 제안한다. 제안된 알고리즘의 성능을 시험하기 위해 SAR 영상 시뮬레이션을 수행하여 성능을 시험하고 검증하였다. 마지막으로 Cosmo-Skymed과 다목적실용위성-5 영상에 각각 적용하여 검증하고 비교한 결과를 제시한다.

Keywords

References

  1. Bovolo, F., C. Marin, and L. Bruzzone, 2013a. A Hierarchical Approach to Change Detection in Very High Resolution SAR Images for Surveillance Applications, IEEE Transactions on Geoscience and Remote Sensing, 51(4): 2042-2054. https://doi.org/10.1109/TGRS.2012.2223219
  2. Choi C.U., C.H. Lee, and Y.C. Suh, 2009. Analytic techniques for change detection using Landsat, Journal of the Korean Association of Geographic Information Studies, 12(3): 13-20.
  3. DeVore M.D. and J.A. O'Sullivan, 2001. Statistical Assessment of Model Fit for Synthetic Aperture Radar Data, SPIE4382, Algorithms for Synthetic Aperture Radar Imagery VIII, 379.
  4. Gao, G., 2010. Statistical Modeling of SAR Images: A Survey, Sensors 2010, 10: 775-795.
  5. Greco, M.S. and F. Gini, 2007. Statistical Analysis of High-Resolution SAR Ground Clutter Data, IEEE Transactions on Geoscience and Remote sensing, 45(3):556-575.
  6. Kim, D.S., Y.I. Kim, and P.M. Wook, 2011. Unsupervised Change Detection of Hyperspectral images Using Range Average and Maximum Distance Methods, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 29(1): 71-80. https://doi.org/10.7848/ksgpc.2011.29.1.71
  7. Kittler, J. and J. Illingworth, 1986. Minimum error thresholding, Pattern Recognition, 19: 41-47. https://doi.org/10.1016/0031-3203(86)90030-0
  8. Krylov, V.A., G. Moser, S.B. Serpico, and J. Zerubia, 2013b. On the Method of Logarithimic Cumulants for Parametric Probability Density Function Estimation, IEEE Transactions on Image Processing, 22(10): 3791-3806. https://doi.org/10.1109/TIP.2013.2262285
  9. Marin, C., F. Bovolo, and L. Bruzzone, 2015. Building change detection in Multitemporal very high resolution SAR Images, IEEE Transactions on Geoscience and Remote Sensing, 53(5): 2664-2682. https://doi.org/10.1109/TGRS.2014.2363548
  10. Moser, G. and S.B. Serpico, 2006. Generalized Minimum-Error Thresholding for Unsupervised Change Detection From SAR Amplitude Imagery, IEEE Transactions on Geoscience and Remote sensing, 44(10): 2972-2982. https://doi.org/10.1109/TGRS.2006.876288
  11. Nicolas, J.M. amd S.N. Anfinsen, 2002. Introduction to Second Kind Statistics: Application of Log-Moments and Log-Cumulants to Analysis of Radar Images, Traitement du Signal (in French), 19(3): 139-167.
  12. Oh, C.Y., S.Y. Park, C.U. Choi, and S.W. Jeon, 2010a. Change Detection at the Nakdong Estuary Delta Using Satellite Image and GIS, Journal of the Korean Society for GeoSpatial Information System, 18(1): 21-29.
  13. Ouchi, K., 2009, Principles of Synthetic Aperture Radar for Remote sensing, Tokyo Denki University Press, Tokyo, Japan
  14. Rignot, E.J.B. and J.J. van Zyl, 1993. Change Detection Techniques for ERS-1 SAR Data, IEEE Transaction on geoscience and Remote Sensing, 31(4): 896-906. https://doi.org/10.1109/36.239913
  15. Sanli ,F.B., Y. Kurucu, M.T. Esetlili, and S. Abdikan, 2008. Soli moisture estimation from RADARSAT-1, ASAR and PALSAR data in agricultural fields of menemen plane of estern Turkey, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing, Vol. 37, Part B7.
  16. Wang, B., S.G. Choi, J.W. Choi, S.C. Yang, Y.G. Byun, and K.S. Park, 2013. Comparison of Change Detection Accuracy based on VHR images Corresponding to the Fusion Estimation Indexes, Journal of the Korean Society for Geospatial Information System, 21(2): 63-69 (in Korean with English abstract). https://doi.org/10.7319/kogsis.2013.21.2.063

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