Browse > Article
http://dx.doi.org/10.7780/kjrs.2015.31.6.7

Reduction of Spectral Distortion in PAN-sharpening Using Spectral Adjustment and Anisotropic Diffusion  

Lee, Sanghoon (Gachon University)
Publication Information
Korean Journal of Remote Sensing / v.31, no.6, 2015 , pp. 571-582 More about this Journal
Abstract
This paper proposes a scheme to reduce spectral distortion in PAN-sharpening which produces a MultiSpectral image (MS) with the higher resolution of PANchromatic image (PAN). The spectral distortion results from reconstructing spatial details of PAN image in the MS image. The proposed method employs Spectral Adjustment and Anisotropic Diffusion to make a reduction of the distortion. The spectral adjustment makes the PAN-sharpened image agree with the original MS image, but causes block distortion because the spectral response of a pixel in the lower resolution is assumed to be equal to the average response of the pixels belonging to the corresponding area in the higher resolution at a same wavelength. The block distortion is corrected by the anisotropic diffusion which uses a conduct coefficient estimating from a local computation of PAN image. It results in yielding a PAN-sharpened image with the spatial structure of PAN image. GSA is one of PAN-sharpening techniques which are efficient in computation as well as good in quantitative quality evaluation. This study suggests the GSA as a preliminary PAN-sharpening method. Two data sets were used in the experiment to evaluate the proposed scheme. One is a Dubaisat-2 image of $1024{\times}1024$ observed at Los Angeles area, USA on February, 2014, the other is an IKONOS of $2048{\times}2048$ observed at Anyang, Korea on March, 2002. The experimental results show that the proposed scheme yields the PAN-sharpened images which have much less spectral distortion and better quantitative quality evaluation.
Keywords
PAN-sharpening; Spectral Adjustment; Anisotropic Diffusion; Spectral Distortion; Spatial Distortion; GSA; Dubaisat-2; IKONOS;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
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, IEEE Transactions on Geoscience and Remote Sensing, 40(10): 2300-2312.   DOI
2 Aiazzi, B., L. Alparone, S. Baronti, A. Garzelli, and M. Selva, 2006. MTFtailored multiscale fusion of high-resolution MS and Pan imagery, Photogrammetric Engineering of Remote Sensing, 72(5): 591-596.   DOI
3 Aiazzi, B., S. Baronti, and M. Selva, 2007. Improving component substitution pansharpening through multivariate regression of MS+Pan data, IEEE Transactions on Geoscience and Remote Sensing, 45(10): 3230-3239.   DOI
4 Alparone, L., L. Wald, J. Chanussot, C. Thomas, P. Gamba, and L.M. Bruce, 2007. Comparison of pansharpening algorithms: Outcome of the 2006 GRS-S data-fusion contest, IEEE Transactions on Geoscience and Remote Sensing, 45(10): 3012-3021.   DOI
5 Alparone L., B. Aiazzi, S. Baronti, A. Garzelli, F. Nencini, and M. Selva, 2008. Multispectral and panchromatic data fusion assessment without reference, Photogrammetric Engineering Remote Sensing, 74(2): 193-200.   DOI
6 Burt, P.J. and E.H. Adelson, 1983. The Laplacian pyramid as a compact image code, IEEE Transactions on Communications, COM-31(4): 532-540.   DOI
7 Carper, W., T. Lillesand, and R. Kiefer, 1990. The use of intensity-hue-saturation transformations for merging Spot panchromatic and multispectral image data, Photogrammetric Engineering Remote Sensing, 56(4): 459-467.
8 Chavez, Jr., P.S. and A.W. Kwarteng, 1989. Extracting spectral contrast in Landsat thematic mapper image data using selective principal component analysis, Photogrammetric Engineering Remote Sensing, 55(3): 339-348.
9 Chavez, P.S., S.C. Sildes, and J.A. Anderson, 1991. Comparison of three different methods to merge multiresolution and multispectral data: Landsat TM and SPOT panchromatic, Photogrammetric Engineering Remote Sensing, 57(3): 295-303.
10 Choi, J., K. Yu, and Y. Kim, 2011. A new adaptive component-substitution based satellite image fusion by using partial replacement, IEEE Transactions on Geoscience and Remote Sensing, 49(1): 295-309.   DOI
11 Garzelli, A., F. Nencini, and L. Capobianco, 2008. Optimal MMSE pan sharpening of very high resolution multispectral images, IEEE Transactions on Geoscience and Remote Sensing, 46(1): 228-236.   DOI
12 Laben, C.A. and B.V. Brower, 2000. Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening, U.S. Patent 6 011 875.
13 Mallat, S., 1989. A theory for multiresolution signal decomposition: The wavelet representation, IEEE Transactions on Pattern Analysus and Machine Intelligence, 11(7): 674-693.   DOI
14 Nason, G.P. and B.W. Silverman, 1995. The stationary wavelet transform and some statistical applications, in Wavelets and Statistics, Springer-Verlag, New York, NY, USA 103: 281-299.
15 Oh, K.Y., H.S. Jung, and N.K. Jeong, 2014. Pansharpening Method for KOMPSAT-2/3 High-Spatial Resolution Satellite Image. Korean Journal of Remote Sensing, 31(2): 161-170. (In Korean with English Abstract)   DOI
16 Perona, P. and J. Malik, 1990. Scale-space and edge detection using anisotropic diffusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(7): 629-639.   DOI
17 Shah, V.P., N.H. Younan, and R.L. King, 2008. An efficient pan-sharpening method via a combined adaptive-PCA approach and contourlets, IEEE Transactions on Geoscience and Remote Sensing, 46(5): 1323-1335.   DOI
18 Vivone, G., R. Restaino, M. Dalla Mura, G. Licciardi, and J. Chanussot, 2014. Contrast and error-based fusion schemes for multispectral image pansharpening, IEEE Transactions on Geoscience and Remote Sensing Letters, 11(5): 930-934.   DOI
19 Shensa, M.J., 1992. The discrete wavelet transform: Wedding the-trous and Mallat algorithm, IEEE Transactions on Signal Processing, 40(10): 2464-2482.   DOI
20 Shettigara, V.K., 1992. A generalized component substitution technique for spatial enhancement of multispectral images using a higher resolution data set, Photogrammetric Engineering Remote Sensing, 58(5): 561-567.
21 Vivone, G., L. Alparone, J. Chanussot, M. Dalla Mura., A. Garzelli, .G.A. Licciardi, R. Restaino, and L. Wald, 2015. A Critical Comparison Among Pansharpening Algorithms, IEEE Transactions on Geoscience and Remote Sensing, 53(5): 2565-2585.   DOI
22 Wald, L., T. Ranchin, and M. Mangolini, 1997. Fusion of satellite images of different spatial resolutions: Assessing the quality of resulting images, Photogrammetric Engineering of Remote Sensing, 63(6): 691-699.