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A Worldview-2 satellite imagery pansharpening algorithm for minimizing the effects of local displacement

지역적 변위에 따른 영향을 최소화하기 위한 Worldview-2 위성영상의 융합 기법

  • 최재완 (충북대학교 공과대학 토목공학부)
  • Received : 2011.10.10
  • Accepted : 2011.11.09
  • Published : 2011.12.31

Abstract

In remote sensing, spatial/spectral distortions are recognized as two of the main problems in the pansharpening algorithm. Most pansharpening methodologies show a tendency to distort spatial information from objects such as buildings and vehicles because there are local spatial dissimilarities among multispectral bands in Worldview-2 satellite imagery. In this paper, we propose a new pansharpening algorithm in order to minimize the effects of the local displacement of spatial information in the pansharpening process. In experiments using Worldview-2 images, our method provided better spectral and spatial quality than pre-existing pansharpening methods.

원격탐사에서 분광 및 공간정보가 왜곡되는 현상들은 영상융합 알고리즘의 가장 큰 문제점으로 알려져 있다. 특히, Worldview-2 위성영상은 멀티스펙트럴 밴드 간 공간정보의 지역적인 비유사성이 존재하기 때문에, 기존의 융합 기법에 의한 융합영상들은 건물이나 차량 등의 개체 등의 공간정보가 왜곡되는 문제를 지닌다. 본 연구에서는 Worldview-2 위성영상의 융합과정에서 발생하는 공간정보의 지역적 변위를 최소화하기 위한 융합 기법을 제안하였다. Worldview-2 위성영상에 제안된 기법을 적용한 결과, 기존의 영상 융합기법에 비하여 분광 정보 및 공간정보의 품질이 향상된 융합영상을 생성할 수 있음을 확인하였다.

Keywords

References

  1. 최재완, 김대성, 김용일 (2011), 공간상관도 기법에 따른 하이브리드 융합영상의 공간/분광 왜곡 평가, 한국측량학회지, 한국측량학회, 제 29권, 제 2호, pp.175-181.
  2. Aiazzi, B., Alparone, L., Baronti, S., Garzelli, A., and Selva, M. (2006), MTF-tailored multiscale fusion of high-resolution MS and Pan imagery, Photogrammetric Engineering & Remote Sensing, Vol. 72, No. 5, pp. 591-596. https://doi.org/10.14358/PERS.72.5.591
  3. Aiazzi, B., Baronit, S., Lotti, F., and Selva, M. (2009), A comparison between global and context-adaptive pansharpening of multispectral images, IEEE Geoscience and Remote Sensing Letters, Vol. 6, No. 2, pp. 302-306. https://doi.org/10.1109/LGRS.2008.2012003
  4. Alparone, L., Wald, L., Chanussot, J., Thomas, C., Gamba, O., and Mann Bruce, L. (2007), Comparison of pansharpening algorithms: outcome of the 2006 GRS-S Data-Fusion contest, IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, No. 10, pp. 3012-3021. https://doi.org/10.1109/TGRS.2007.904923
  5. Baronti, S., Aiazzi, B., Selva, M., Garzelli, and Alparone, L. (2011), A theoretical analysis of the effects of aliasing and misregistration on pansharpened imagery, IEEE Journal of Selected Topics in Signal Processing, Vol. 5, No. 3, pp. 446-453. https://doi.org/10.1109/JSTSP.2011.2104938
  6. Fasbender, D., Radoux, J., and Bogaert, P. (2008), Bayesian data fusion for adaptable image pansharpening, IEEE Transactions on Geoscience and Remote Sensing, Vol. 46, No. 6, pp. 1847-1857. https://doi.org/10.1109/TGRS.2008.917131
  7. Ling, Y., Ehlers, M., Usery, E. L., and Madden, M. (2007), FFT-enhanced IHS transform method for fusing high-resolution satellite images, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 61, pp. 381-392. https://doi.org/10.1016/j.isprsjprs.2006.11.002
  8. Tu, T. M., Huang, P. S., Hung, C. L., and Chang, C. P. (2004), A fast Intensity-Hue-Saturation fusion technique with spectral adjustment for IKONOS imagery, IEEE Geoscience and Remote Sensing Letters, Vol. 1, No. 4, pp. 309-312. https://doi.org/10.1109/LGRS.2004.834804
  9. Zhang, Y. (2004), Understanding image fusion, Photogrammetric Engineering & Remote Sensing, Vol. 70, No. 6, pp. 653-660.
  10. Zhou, J., Civco, D. L., and Silander, J. A. (1998), A wavelet transform method to merge Landsat TM and SPOT panchromatic data, International Journal of Remote Sensing, Vol. 19, No. 4, pp. 743-757. https://doi.org/10.1080/014311698215973

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