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Pan-Sharpening Algorithm of High-Spatial Resolution Satellite Image by Using Spectral and Spatial Characteristics  

Choi, Jae-Wan (서울대학교 공과대학 건설환경공학부 공간정보연구실)
Kim, Yong-Il (서울대학교 공과대학 건설환경공학부)
Publication Information
Journal of Korean Society for Geospatial Information Science / v.18, no.2, 2010 , pp. 79-86 More about this Journal
Abstract
Generally, image fusion is defined as generating re-organized image by merging two or more data using special algorithms. In remote sensing, image fusion technique is called as Pan-sharpening algorithm because it aims to improve the spatial resolution of original multispectral image by using panchromatic image of high-spatial resolution. The pan-sharpened image has been an important task due to various applications such as change detection, digital map creation and urban analysis. However, most approaches have tended to distort the spectral information of the original multispectral data or decrease the spatial quality compared with the panchromatic image. In order to solve these problems, a novel pan-sharpening algorithm is proposed by considering the spectral and spatial characteristics of multispectral image. The algorithm is applied to the KOMPSAT-2 and QuickBird satellite image and the results showed that our method can improve the spectral/spatial quality compared with the existing fusion algorithms.
Keywords
Pan-sharpening; spatial quality decrease; spectral distortion; spectral and spatial characteristics; image fusion;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 최재완, 김형태, 2008, "수정된 영상 유도 기법을 통한융합영상의 분광정보 향상 알고리즘", 지형공간정보, 한국지형공간정보학회지, 제 16권, 3호, pp. 15-20.
2 T. M. Tu, P. S. Huang, C. L. Hung, and C. P.Chang, 2004, "A fast intensity- hue-saturation fusiontechnique with spectral adjustment for IKONOSimagery", IEEE Transactions on Geoscience andRemote Sensing Letters, Vol.1, No.4, pp.309-312.   DOI   ScienceOn
3 M. Gonzalez-Audicana, X. Otazu, O. Fors and A.Seco, 2005, "Comparison between Mallat's and thea'trous discrete wavelet transformation basedalgorithms for the fusion of multispectral andpanchromatic images", International Journal ofRemote Sensing, Vol.26, No.3, pp.595-614.   DOI   ScienceOn
4 J. Lee, and C. Lee, 2010, "Fast and EfficientPanchromatic Sharpening", IEEE Transactions onGeoscience and Remote Sensing, Vol.48, No.1, pp.155-163.   DOI
5 B. Aiazzi, L. Alparone, S. Baronti, A. Garzeli, and M.Selva, 2006, "MTF-tailored multiscale fusion ofhigh-resolution MS and Pan imagery", Photogramm. Eng. Remote Sens., Vol.72, No.5, pp.591-596.   DOI
6 Aiazzi, S. Baronti, F. Lotti, and M. Selva, 2009,"A comparison between global and context-adaptivepansharpening of multispectral images", IEEE Transactions on Geoscience and Remote SensingLetters, Vol.6, No.2, pp.302-306.   DOI
7 C. A. Laben, and B. V. Brower, 2000, "Process forenhancing the spatial resolution of multispectralimagery using pan-sharpening", U.S. Patent6011875, Tech. Rep., Eastman Kodak Company.
8 L. Alparone, B. Aiazzi, S. Baronti, and A. Garzelli, 2003, "Sharpening of very high resolution imageswith spectral distortion minimization", Proc. IGARSS, pp.21-25.
9 J. Nunez, X. Otazu, O. Fors, A. Prade, V. Pala, and R. Arbiol, 1999, "Multiresolution-based image fusion with additivie wavelet decomposition", IEEE Transactions on Geoscience and Remote Sensing, Vol.37, No.3, pp.1204-1211.   DOI   ScienceOn
10 J. Zhou, D. L. Civco, and J. A. Silander, 1998, "Awavelet transform method to merge Landsat TMand SPOT panchromatic data", InternationalJournal of Remote Sensing, Vol.19, No.4, pp.743-757.   DOI   ScienceOn
11 L. Alparone, S. Baronti, A. Garzelli, and F. Nencini, 2004, "A global quality measurement of pansharpened multispectral imagery", IEEE Transactions on Geoscience and Remote Sensing Letters, Vol.1, No.4, pp.313-317.   DOI   ScienceOn
12 L. Alparone, L. Wald, J. Chanusot, C. Thoma, O.Gamaba, and L. Mann Bruce, 2007, "Comparison ofpan-sharpening algorithms: outcome of the 2006GRS-S Data-Fusion Contest", IEEE Transactionson Geoscience and Remote Sensing, Vol.45,No.10, pp.3012-3021.   DOI
13 M. Gonzalez-Audicana, X. Otazu, O. Fors, and J. A.Alvarex-Mozos, 2006, "A low computational-costmethod to fuse IKONOS images using the spectralresponse function of its sensors", IEEETransactions on Geoscience and Remote Sensing, Vol.44, No.6, pp.1683-1691.   DOI
14 W. Dou, Y. Chen, X. Li and D. Z. Sui, 2007, "Ageneral framework for component substitution imagefusion: An implementation using the fast imagefusion method", Computers & Geosciences, Vol.33, pp.219-228.   DOI   ScienceOn
15 X. Otazu, M. Gonzalez-Audicana, O. Fors, and J.Nunez, 2005, "Introdction of sensor spectralresponse into image fusion methods. Application towavelet-based methods", IEEE Transactions on Geoscience and Remote Sensing, Vol.43, No.10,pp.2376-2385.   DOI
16 Y. Zhang, 2004, "Understanding image fusion", Photogrammetric Engineering & Remote Sensing, Vol.70, No.6, pp.653-660.