Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회지)

Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회)
권호 표지
DOI QR코드

DOI QR Code

Image Fusion of High Resolution SAR and Optical Image Using High Frequency Information

고해상도 SAR와 광학영상의 고주파 정보를 이용한 다중센서 융합

  • 변영기 (한국항공우주연구원 위성정보 연구센터) ;
  • 채태병 (한국항공우주연구원 위성정보 연구센터.영상운영지원팀)
  • Received : 2012.01.30
  • Accepted : 2012.02.20
  • Published : 2012.02.29
Download PDF
⟨ Previous Next ⟩

Abstract

Synthetic Aperture Radar(SAR) imaging system is independent of solar illumination and weather conditions; however, SAR image is difficult to interpret as compared with optical images. It has been increased interest in multi-sensor fusion technique which can improve the interpretability of $SAR^{\circ\circ}$ images by fusing the spectral information from multispectral(MS) image. In this paper, a multi-sensor fusion method based on high-frequency extraction process using Fast Fourier Transform(FFT) and outlier elimination process is proposed, which maintain the spectral content of the original MS image while retaining the spatial detail of the high-resolution SAR image. We used TerraSAR-X which is constructed on the same X-band SAR system as KOMPSAT-5 and KOMPSAT-2 MS image as the test data set to evaluate the proposed method. In order to evaluate the efficiency of the proposed method, the fusion result was compared visually and quantitatively with the result obtained using existing fusion algorithms. The evaluation results showed that the proposed image fusion method achieved successful results in the fusion of SAR and MS image compared with the existing fusion algorithms.

SAR는 기상상태와 태양고도 제약을 받지 않고 영상을 취득할 수 있는 장점을 갖지만 광학영상에 비해 시각적 가독성이 떨어지는 단점을 갖는다. 광학영상의 다중분광정보를 융합하여 SAR 영상의 가독성을 향상시키기 위한 다중센서 융합기술에 대한 관심이 증대되고 있다. 본 연구에서는 고속 퓨리에 변환을 통한 고주파 정보 추출 및 이상치 제거과정을 통해 SAR 영상의 공간적 세밀함과 다중분광영상의 분광정보를 유지할 수 있는 새로운 다중센서 융합기술을 제안하였다. 실험데이터로는 KOMPSAT-5호와 동일한 고해상도 X-band SAR 시스템을 장착한 TerraSAR-X 영상과 KOMPSAT-2호의 다중분광영상을 사용하였다. 제안기법의 효용성을 평가하기 위해 기존에 위성영상융합에 많이 사용된 융합기법과의 시각적/정량적 비교평가를 수행하였다. 실험 결과 기존 영상융합알고리즘에 비해 분광정보 보존측면에서 보다 향상된 결과를 보임을 확인할 수 있었다.

Keywords

References

  1. 변영기, 채태병 (2011), 결정론적 영상복원과정을 이용한 고해상도 위성영상 융합 품질 개선정도 평가, 한국측량학회지, 한국측량학회, 제 29권, 제 5호, pp. 471-479.
  2. 한유경, 변영기, 채태병, 김용일 (2011), KOMPSAT-2 영상과 TerraSAR-X 영상 간 자동기하보정, 한국측량학회지, 한국측량학회, 제 29권, 제 6호, pp. 441-449.
  3. 최재완, 김대성, 김용일 (2011), 공간 상관도 기법에 따른 하이브리드 융합영상의 공간/분광 왜곡평가, 한국측량학회지, 한국측량학회, 제 29권, 제 2호, pp. 175-181.
  4. Alparone, L., Baronti, S., Garzelli, A., and Nencini, F. (2004), Landsat ETM+ and SAR image fusion based on generalized intensity modulation, IEEE Transactions on Geoscience and Remote Sensing, Vol. 42, No. 12, pp. 2832-2839. https://doi.org/10.1109/TGRS.2004.838344
  5. Ban, Y., Hu, H., and Rangel, I. M. (2010), Fusion of QuickBird MS and Radarsat SAR data for urban land cover mapping: object-based and knowledge-based approach, International Journal of Remote Sensing, Vol. 31, No. 6, pp. 1391-1410. https://doi.org/10.1080/01431160903475415
  6. Chibani, Y. (2007), Integration of panchromatic and SAR features into multispectral SPOT images using the àtrous wavelet decomposition, International Journal of Remote Sensing, Vol. 28, No. 10, pp.2295-2307. https://doi.org/10.1080/01431160600606874
  7. Dou, W., Chen, Y., Li, X., and Sui, D. Z. (2007), A general framework for component substitution image fusion; An implementation using the fast fusion method, Computers and Geoscience, Vol. 33, pp. 219-228. https://doi.org/10.1016/j.cageo.2006.06.008
  8. Gonzalez, R. C., and Woods, R. E. (2002), Digital image processing, Prientice-Hall, New Jersey, pp. 208-213.
  9. Hong, G., Zhang, Y., and Mercer, B. (2009), A wavelet and IHS Integration Method to fuse high resolution SAR with moderate resolution multispectral images, Photogrammetric Engineering and Remote Sensing, Vol. 75, No. 10, pp. 1213-1223. https://doi.org/10.14358/PERS.75.10.1213
  10. Huang, T. S. (1978), Two-dimensional Windows, IEEE Transaciton On Audio and Electroacoustics, Vol. 20, No. 5, pp. 260-269.
  11. Huynh, T. Q., and Ghanbari, M. (2008), Scope of validity of PSNR in image/video quality assessment, Electronics Letters, Vol. 44, No. 13, pp. 800-801. https://doi.org/10.1049/el:20080522
  12. Lee, J. S. (1980), Digital image enhancement and noise filtering by use of local statistics, IEEE Pattern Analysis and Machine Intelligence, Vol. 2, No. 2, pp. 165-168.
  13. Ling, Y., Ehlers, M., Lynn Usery, E., and Madden, M. (2007), FFT-enhanced IHS transform method for fusing high-resolution satellite images, Photogrammetric Engineering and Remote Sensing, Vol. 61, No. 6, pp. 381-392. https://doi.org/10.1016/j.isprsjprs.2006.11.002
  14. Nunez, J., Otazu, X., Fors, O., Prade, A., Pala, V., and Arbiol, R. (1999), Multiresolution-based image fusion with additive wavelet decomposition, IEEE Transactions on Geoscience and Remote Sensing, Vol. 37, No. 3, pp. 1204-1211. https://doi.org/10.1109/36.763274
  15. Otazu, X., Gonzálaz-Audícana, M., Fors, O., and Núnez, J. (2005), Introduction of sensor spectral response into image fusion method. Application to wavelet-based method, IEEE Transactions on Geoscience and Remote Sensing, Vol. 43, No. 10, pp. 2376-2385. https://doi.org/10.1109/TGRS.2005.856106
  16. Pohl, C., and van Genderen, J. L. (1998), Multisensor image fusion in remote sensing: Concepts, methods, and application, International Journal of Remote Sensing, Vol. 19, No. 5, pp. 825-854.
  17. Ranchin, T., and Wald, L. (2000), Fusion of High Spatial and Spectral Resolution Images: The ARSIS Concept and Its application, Photogrammetric Engineering and Remote Sensing, Vol. 66, No. 1, pp. 49-61.
  18. Solberg, A. H. S., Taxt, T., and Jain, A. K. (1996), A Markov random field model for classification of multisource satellite imagery, IEEE Transactions on Geoscience and Remote Sensing, Vol. 34, No. 1, pp. 100-113. https://doi.org/10.1109/36.481897
  19. Wang, Z., and Bovik, A.C. (2002), Universal Image Quality Index, IEEE Signal Processing Letters, Vol. 9, No. 3, pp. 81-84. https://doi.org/10.1109/97.995823
  20. Zhang, W., and Yu, L. (2010), SAR and Landsat ETM+ image fusion using variational model, Computer and Communication Technologies in Agriculture Engineering, IEEE, Chengdu pp. 205-207.
  21. Zitova, B., and Flusser, J. (2003), Image registration method: a survey, Image and Vision Computing, Vol. 21, No. 11, pp. 977-1000. https://doi.org/10.1016/S0262-8856(03)00137-9

Cited by

  1. IR and SAR Sensor Fusion based Target Detection using BMVT-M vol.21, pp.11, 2015, https://doi.org/10.5302/J.ICROS.2015.15.0147
  2. DEM 품질에 따른 고해상도 SAR 영상의 지형 보정 정확도 평가 vol.30, pp.6, 2012, https://doi.org/10.7848/ksgpc.2012.30.6-1.519