Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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Comparative Analysis of Image Fusion Methods According to Spectral Responses of High-Resolution Optical Sensors

고해상 광학센서의 스펙트럼 응답에 따른 영상융합 기법 비교분석

  • 이하성 (서울시립대학교 공간정보공학과) ;
  • 오관영 (서울시립대학교 공간정보공학과) ;
  • 정형섭 (서울시립대학교 공간정보공학과)
  • Received : 2014.02.20
  • Accepted : 2014.04.12
  • Published : 2014.04.30
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Abstract

This study aims to evaluate performance of various image fusion methods based on the spectral responses of high-resolution optical satellite sensors such as KOMPSAT-2, QuickBird and WorldView-2. The image fusion methods used in this study are GIHS, GIHSA, GS1 and AIHS. A quality evaluation of each image fusion method was performed with both quantitative and visual analysis. The quantitative analysis was carried out using spectral angle mapper index (SAM), relative global dimensional error (spectral ERGAS) and image quality index (Q4). The results indicates that the GIHSA method is slightly better than other methods for KOMPSAT-2 images. On the other hand, the GS1 method is suitable for Quickbird and WorldView-2 images.

본 연구는 서로 다른 센서 특성을 지닌 KOMPSAT-2, QuickBird 및 WorldView-2 고해상도 위성영상에 영상융합기법을 적용하여 그 결과를 비교평가 하는 것이다. 사용된 기법은 대표적인 CS 기반 융합기법인 GIHS, GIHSA, GS1 및 Adaptive IHS를 사용하였다. 영상융합 기법의 품질평가는 시각적 분석과 정량적 분석을 수행하였으며, 정량적 분석에는 SAM, Spectral ERGAS 및 Q4을 사용하였다. KOMPSAT-2 영상은 GHISA 기법의 경우 상대적으로 우수한 성능을 나타내는 반면, QuickBird와 WorldView-2영상은 GS1기법의 경우에 우수한 성능을 나타낸다.

Keywords

References

  1. Aiazzi, B., L. Alparone., S. Baronti. and A. Garzelli, 2002. Context-driven fusion of high spatial and spectral resolution images based on oversampled multiresolution analysis, Geoscience and Remote Sensing, IEEE Transactions on, 40(10): 2300-2312. https://doi.org/10.1109/TGRS.2002.803623
  2. Aiazzi, B., S. Baronti. and M. Selva, 2007. Improving component substitution pansharpening through multivariate regression of MS+ Pan data, Geoscience and Remote Sensing, IEEE Transactions on, 45(10): 3230-3239. https://doi.org/10.1109/TGRS.2007.901007
  3. Alparone, L., S. Baronti., A. Garzelli. and F. Nencini, 2004. A global quality measurement of pan-sharpened multispectral imagery, Geoscience and Remote Sensing Letters, IEEE, 1(4): 313-317. https://doi.org/10.1109/LGRS.2004.836784
  4. Choi, J.W. and Y.I. Kim, 2010. Pan-Sharpening Algorithm of High-Spatial Resolution Satellite Image by Using Spectral and Spatial Characteristics, Journal of the Korean Society for Geospatial Information System, 18(2): 79-86.
  5. Choi, J.W, 2011. A WorldView-2 satellite imagery pansharpening algorithm for minimizing the effects of local displacement, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 29(6): 577-582. https://doi.org/10.7848/ksgpc.2011.29.6.577
  6. Choi. J.W., J. Yom., A. Chang., Y. Byun. and Y. Kim, 2013. Hybrid Pansharpening Algorithm for High Spatial Resolution Satellite Imagery to Improve Spatial Quality, Geoscience and Remote Sensing Letters, IEEE, 10(3): 490-494. https://doi.org/10.1109/LGRS.2012.2210857
  7. Choi, M.J., H.C. Kim., N.I. Cho. and H.O. Kim, 2006. An improved intensity-hue-saturation method for IKONOS image fusion, International Journal of Remote Sensing, 1(2).
  8. Dou, W., Y. Chen., X. Li. and D.Z. Sui, 2007. A general framework for component substitution image fusion: An implementation using the fast image fusion method, Computers and Geosciences, 33(2): 219-228. https://doi.org/10.1016/j.cageo.2006.06.008
  9. KIm, Y., E. Yangdam., Y. Kim. and Y. Kim, 2011. Generalized IHS-Based Satellite imagery Fusion Using Spectral Response Functions, ETRI Journal, 3(4): 497-505. https://doi.org/10.4218/etrij.11.1610.0042
  10. Kruse, F.A., A.B. Lefkoff., J.W. Boardman., K.B. Heidebrecht., A.T. Shapiro., P.J. Barloon. and A. F.H. Goetz, 1993. The spectral image processing system (SIPS) interactive visualization and analysis of imaging spectrometer data, Remote Sensing of Environment, 44(2): 145-163. https://doi.org/10.1016/0034-4257(93)90013-N
  11. Oh, K.Y., H.S. Jung. and K.J. Lee, 2012. Comparison of image Fusion Methods to Merge KOMPSAT-2 Panchromatic and Multispectral Images, Korean Journal of Remote Sensing, 28(1): 39-54. https://doi.org/10.7780/kjrs.2012.28.1.039
  12. Perona, P. and J. Malik, 1990. Scale-space and edge detection using anisotropic diffusion, Pattern Analysis and Machine Intelligence, IEEE Transactions on, 12(7): 629-639. https://doi.org/10.1109/34.56205
  13. Ranchin, T. and L. Wald, 2000. Fusion of high spatial and resolution images: the ARSIS concept and its implementation, Photogrammetric Engineering and Remote Sensing, 66(1): 49-61.
  14. Rahmani, S., M. Strait., D. Merkurjev., M. Moeller. and T. Wittman, 2010. An adaptive IHS pan-sharpening method, Geoscience and Remote Sensing Letters, IEEE, 7(4): 746-750. https://doi.org/10.1109/LGRS.2010.2046715
  15. Saacedra, M.L. and C. Gonzalo, 2006. Spectral or spatial quality for fused satellite imagery? A trade-off solution using the wavelet a'trous algorithm, International Journal of Remote Sensing, 27(7): 1453-1464. https://doi.org/10.1080/01431160500462188
  16. Tu, T.M., C.L. Hsu., P.Y. Tu., and C.H. Lee, 2012. An adjustable pan-sharpening approach for IKONOS/QuickBird/GeoEye-1/WorldView-2 imagery. Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 5(1): 125-134. https://doi.org/10.1109/JSTARS.2011.2181827
  17. Tu, T.M., P.S. Huang., C.L. Hung. and C.P. Chang, 2004. A fast intensity-hue-saturation fusion technique with spectral adjustment for IKONOS imagery, Geoscience and Remote Sensing Letters, IEEE, 1(4): 309-312. https://doi.org/10.1109/LGRS.2004.834804
  18. Wald, L., T. Ranchin. and M. Mangolini, 1997. Fusion of Satellite Images of Different Spatial Resolutions: Assessing the Quality of Resulting Images, Photogrammetric Engineering and Remote sensing, 63(6): 691-699.
  19. Zhang, Y., 2004. Understanding image fusion, Photogrammetric Engineering and Remote Sensing, 70(6): 657-661.

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