Journal of Korean Society for Geospatial Information Science (대한공간정보학회지)

Korea Spatial Information Society (대한공간정보학회)
권호 표지
DOI QR코드

DOI QR Code

Comparison of Change Detection Accuracy based on VHR images Corresponding to the Fusion Estimation Indexes

융합평가 지수에 따른 고해상도 위성영상 기반 변화탐지 정확도의 비교평가

  • Wang, Biao (Department of Civil Engineering, Chungbuk National University) ;
  • Choi, Seok Geun (Department of Civil Engineering Chungbuk National University) ;
  • Choi, Jae Wan (Department of Civil Engineering Chungbuk National University) ;
  • Yang, Sung Chul (Spatial Information Research Institute) ;
  • Byun, Young Gi (Korea Aerospace Research Institute) ;
  • Park, Kyeong Sik (Department of Aerial Geoinformatics, Inha Technical College)
  • ;
  • 최석근 (충북대학교 공과대학 토목공학부) ;
  • 최재완 (충북대학교 공과대학 토목공학부) ;
  • 양성철 (공간정보연구원) ;
  • 변영기 (한국항공우주연구원 위성정보 연구센터) ;
  • 박경식 (인하공업전문대학교 항공정보지리과)
  • Received : 2013.04.12
  • Accepted : 2013.06.21
  • Published : 2013.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

Change detection technique is essential to various applications of Very High-Resolution(VHR) satellite imagery and land monitoring. However, change detection accuracy of VHR satellite imagery can be decreased due to various geometrical dissimilarity. In this paper, the existing fusion evaluation indexes were revised and applied to improve VHR imagery based change detection accuracy between multi-temporal images. In addition, appropriate change detection methodology of VHR images are proposed through comparison of general change detection algorithm with cross-sharpened image based change detection algorithm. For these purpose, ERGAS, UIQI and SAM, which were representative fusion evaluation index, were applied to unsupervised change detection, and then, these were compared with CVA based change detection result. Methodologies for minimizing the geometrical error of change detection algorithm are analyzed through evaluation of change detection accuracy corresponding to image fusion method, also. The experimental results are shown that change detection accuracy based on ERGAS index by using cross-sharpened images is higher than these based on other estimation index by using general fused image.

변화탐지 기법은 위성영상의 활용 및 국토 모니터링에 있어서 필수적인 알고리즘이다. 그러나, 변화탐지 기법을 고해상도 위성영상에 적용할 경우, 다시기 영상 간의 기하학적 차이 등에 의하여 변화탐지 정확도가 저하될 수 있다. 본 연구에서는 효과적인 위성영상의 변화탐지를 위하여 기존의 융합 영상 평가지수를 활용하고자 한다. 또한, 기존의 다시기 위성영상을 활용한 일반적인 변화탐지 기법과 교차융합영상을 이용한 변화탐지 결과를 비교하여, 다시기 고해상도 위성영상에 적합한 변화탐지 기법을 제안하고자 한다. 이를 위해, 융합영상 평가 지수인 ERGAS, UIQI, SAM를 무감독 변화탐지 기법에 적용하고 기존의 CVA를 이용한 변화탐지 기법의 결과와 비교하였다. 또한, 영상융합 기법에 따른 고해상도 위성영상 변화탐지 정확도를 평가하여 고해상도 위성영상의 무감독 변화탐지에서 발생할 수 있는 기하학적 오차를 최소화할 수 있는 방법을 분석하였다. 실험결과, 교차융합영상과 ERGAS 지수를 활용한 변화탐지 기법이 기존 기법과 비교하여 상대적으로 높은 변화지역 탐지 가능성을 가지는 것을 확인할 수 있었다.

Keywords

References

  1. Chen, X., Vierling, L., Deering, D., 2005, A simple and effective radiometric correction method to improve landscape change detection across sensors and across time, Remote Sensing of Environment, Vol. 98, pp. 63-79. https://doi.org/10.1016/j.rse.2005.05.021
  2. Choi, J., Byun, Y., 2012(a), Utilization of a pansharpening quality index for change detection of high resolution satellite image, Conference of The Korean society for GeoSpatial Information System, pp.5-6.
  3. Choi, J., Byun, Y., 2012(b), Effects analysis of the image fusion result by a relief displacement and changed area, Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, pp. 303-304.
  4. Choi, J., Byun, Y., 2012(c), The pansharpening algorithm based on NDVI for generation of satellite digital map with high-spatial resolution, Journal of Cadastre, Vol. 42, No. 2, pp. 213-226.
  5. Lu, D., Mausel, P., Brondizio, E., Moran, E., 2004, Change detection techniques, International Journal of Remote Sensing, Vol. 25, No. 12, pp. 2365-2407. https://doi.org/10.1080/0143116031000139863
  6. Otsu, N., 1979, A threshold selection method from gray level histograms, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 9, No.1, pp. 62-66. https://doi.org/10.1109/TSMC.1979.4310076
  7. Rahmani, S., Strait, M., Merkurijev, D., Moeller, M., Wittman, T., 2010, An adaptive IHS pan-sharpening method, IEEE Geoscience and Remote Sensing Letters, Vol. 7, No. 4, pp. 746-750. https://doi.org/10.1109/LGRS.2010.2046715
  8. Renza, D., Martinez, E., Arquero, A., 2012, A new approach to change detection in multispectral image by means for ERGAS index, IEEE Geoscience and Remote Sensing Letters, Vol. 10, No.1, pp.1-5.
  9. Wang, B., Choi, J., Choi, S., 2012, Cpmparison of unsupervised change detection methods for satellite imagery using fusion quality quality indexes, COnference on Geo-Spatial Information, pp. 77-78.
  10. Zhang, H., Chen, J., Mao, Z., 2009, An operational method to determine change threshold using change vector analysis, Proc. of SPIE Vol. 7497, pp. 749706-1-749706-8.
  11. Zhang, Q., Wang, J., 2002, Detection of buildings from Landsat-7 ETM+ and SPOT panchromatic data in Beijing, China, IEEE Geoscience and Remote Sensing Symposium(IGARSS), Vol. 5, pp. 2977- 2979.