Abstract
A fused image of high spatial and spectral resolutions can be obtained by fusing a panchromatic (PAN) image with a multi-spectral (MS) image. In this paper, a new image fusion method is proposed, based on an intrinsic image decomposition model which assumes that an image can be separated into two components: the reflectance and illumination components. In pansharpening, it is known that the PAN image is a good substitute for the illumination of the ideal high resolution MS image. Therefore, the reflectance of the low resolution MS image can be estimated with the MS image and the downsampled PAN image. Then, through combining the upsampled reflectance component with the high resolution illumination component (the original PAN image), the pansharpened high resolution MS image can be reconstructed. Experiments performed on three data sets captured by different satellite sensors demonstrate that the proposed method can obtain clear fused images without causing a serious spectral distortion. Furthermore, since the proposed method requires dot multiplication, division, downsampling, and upsampling operations to be performed only once, it can be implemented for a very fast performance.








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Kempeneers, P., Sedano, F., Seebach, L., Strobl, P., & San-Miguel-Ayanz, J. (Dec. 2011). Data fusion of different spatial resolution remote sensing images applied to forest-type mapping. IEEE Transactions on Geoscience and Remote Sensing, 49(12), 4977–4986.
Dalponte, M., Bruzzone, L., & Gianelle, D. (May 2008). Fusion of hyperspectral and LIDAR remote sensing data for classification of complex forest areas. IEEE Transactions on Geoscience and Remote Sensing, 46(5), 1416–1427.
Sirguey, P., Mathieu, R., Arnaud, Y., Khan, M. M., & Chanussot, J. (Jan. 2008). Improving MODIS spatial resolution for snow mapping using wavelet fusion and ARSIS concept. IEEE Geoscience and Remote Sensing Letters, 5(1), 78–82.
Liu, J. G. (2000). Smoothing filter-based intensity modulation: a spectral preserve image fusion technique for improving spatial details. International Journal of Remote Sensing, 21(18), 3461–3472.
Nunez, J., Otazu, X., Fors, O., Prades, A., Pala, V., & Arbiol, R. (May 1999). Multiresolution-based image fusion with additive wavelet decomposition. IEEE Transactions on Geoscience and Remote Sensing, 37(3), 1204–1211.
Otazu, X., Gonzalez-Audicana, M., Fors, O., & Nunez, J. (Oct. 2005). Introduction of sensor spectral response into image fusion methods. application to wavelet-based methods. IEEE Transactions on Geoscience and Remote Sensing, 43(10), 2376–2385.
Li, S., Kwok, J. T., & Wang, Y. (Jan. 2002). Using the discrete wavelet frame transform to merge landsat TM and SPOT panchromatic images. Information Fusion, 3(1), 17–23.
Aiazzi, B., Alparone, L., Baronti, S., & Garzelli, A. (Oct. 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.
Mahyari, A. G., & Yazdi, M. (Jun. 2011). Panchromatic and multispectral image fusion based on maximization of both spectral and spatial similarities. IEEE Transactions on Geoscience and Remote Sensing, 49(6), 1976–1985.
Hu, J., & Li, S. (2011). Fusion of panchromatic and multispectral images using multiscale dual bilateral filter. In Proceedings of IEEE international conference on image processing, pp 1489–1492.
Zheng, S., Shi, W., Liu, J., & Tian, J. (May 2008). Remote sensing image fusion using multiscale mapped LS-SVM. IEEE Transactions on Geoscience and Remote Sensing, 46(5), 1313–1322.
Thomas, C., Ranchin, T., Wald, L., & Chanussot, J. (May 2008). Synthesis of multispectral images to high spatial resolution: a critical review of fusion methods based on remote sensing physics. IEEE Transactions on Geoscience and Remote Sensing, 46(5), 1301–1312.
Lee, J., & Lee, C. (Jan. 2010). Fast and efficient panchromatic sharpening. IEEE Transactions on Geoscience and Remote Sensing, 48(1), 155–163.
Zhou, Z., Peng, S., Wang, B., Hao, Z., & Chen, S. (Jul. 2012). An optimized approach for ansharpening very high resolution multispectral images. IEEE Geoscience and Remote Sensing Letters, 9(4), 735–739.
Joshi, M. V., Bruzzone, L., & Chaudhuri, S. (Sep. 2006). A model-based approach to multiresolution fusion in remotely sensed images. IEEE Transactions on Geoscience and Remote Sensing, 44(9), 2549–2562.
Li, S., & Yang, B. (Feb. 2011). A new pan-sharpening method using a compressed sensing technique. IEEE Transactions on Geoscience and Remote Sensing, 49(2), 738–746.
Li, S., Yin, H., & Fang, L. (Sep. 2013). Remote sensing image fusion via sparse representations over learned dictionaries. IEEE Transactions on Geoscience and Remote Sensing, 51(9), 4779–4789.
Zhu, X., & Bamler, R. (May 2013). A sparse image fusion algorithm with application to pan-sharpening. IEEE Transactions on Geoscience and Remote Sensing, 51(5), 2827–2836.
Jiang, C., Zhang, H., Shen, H., & Zhang, L. (Jul. 2012). A practical compressed sensing-based pan-sharpening method. IEEE Geoscience and Remote Sensing Letters, 9(4), 629–633.
Joshi, M., & Jalobeanu, A. (Mar. 2010). MAP estimation for multiresolution fusion in remotely sensed images using an IGMRF prior model. IEEE Transactions on Geoscience and Remote Sensing, 48(3), 1245–1255.
Zhang, L., Shen, H., Gong, W., & Zhang, H. (Dec. 2012). Adjustable model-based fusion method for multispectral and panchromatic images. IEEE Transactions on Systems, Man and Cybernetics. Part B Cybernetics, 42(6), 1693–1704.
Yacoob, Y., & Davis, L. S. (Jul. 2009). Segmentation using appearance of mesostruc-ture roughness. International Journal of Computer Vision, 83(3), 248–273.
Shen, J., Yang, X., Li, X., & Jia, Y. (Mar. 2013). Intrinsic image decomposition using optimization and user scribbles. IEEE Transactions on Cybernetics, 43(2), 425–436.
Barron, J. & Malik, J. (May 2013). Shape, illumination, and reflectance from shading. Technical Report UCB/EECS-2013-117, EECS Department, University of California, Berkeley.
Hanson, A., & Riseman, E. (1978). Computer vision systems. New York: Academic Press.
Tappen, M. F., Freeman, W. T., & Adelson, E. H. (Sep. 2005). Recovering intrinsic images from a single image. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(9), 1459–1472.
Bousseau, A., Paris, S., & Durand, F. (Dec. 2009). User-assisted intrinsic images. ACM Transactions on Graphics, 28(5), 130:1–130:10.
Liu, X., Wan, L., Qu, Y., Wong, T., Lin, S., Leung, C., et al. (Dec. 2008). Intrinsic colorization. ACM Transactions on Graphics, 27(5), 152:1–152:9.
Carper, W. J., Lillesand, T. M., & Kiefer, R. W. (1990). The use of intensity-hue-saturation transformations for merging spot panchromatic and multispectral image data. Photogrammetric Engineering Remote Sensing, 56, 459–467.
Shah, V. P., Younan, N. H., & King, R. L. (May 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.
Nikolakopoulos, Konstantinos G. (2008). Comparison of nine fusion techniques for very high resolution data. Photogrammetric Engineering Remote Sensing, 74(5), 647.
Keys, R. (Dec. 1981). Cubic convolution interpolation for digital image processing. IEEE Transactions on Acoustics, Speech and Signal Processing, 29(6), 1153–1160.
Rahmani, S., Strait, M., Merkurjev, D., Moeller, M., & Wittman, T. (Oct. 2010). An adaptive IHS pan-sharpening method. IEEE Geoscience and Remote Sensing Letters, 7(4), 746–750.
Choi, J., Yu, K., & Kim, Y. (Jan. 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.
Alparone, L., Wald, L., Chanussot, J., Thomas, C., Gamba, P., & Bruce, L. M. (Oct. 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.
Luo, B., Khan, M. M., Bienvenu, T., Chanussot, J., & Zhang, L. (Jan. 2013). Decision-based fusion for pansharpening of remote sensing images. IEEE Geoscience and Remote Sensing Letters, 10(1), 19–23.
Alparone, L., Baronti, S., Garzelli, A., & Nencini, F. (Oct. 2004). A global quality measurement of pan-sharpened multispectral imagery. IEEE Geoscience and Remote Sensing Letters, 1(4), 313–317.
Alparone, L., Aiazzi, B., Baronti, S., Garzelli, A., Nencini, F., & Selva, M. (Feb. 2008). Multispectral and panchromatic data fusion assessment without reference. Photogrammetric Engineering Remote Sensing, 74(2), 193–200.
Wang, Z., & Bovik, A. C. (Mar. 2002). A universal image quality index. IEEE Signal Processing Letters, 9(3), 81–84.
Acknowledgments
The authors would like to thank S. Rahmani and J. Choi for providing the software of the Brovey, AIHS, and CSPR methods. This paper was supported in part by the National Natural Science Foundation for Distinguished Young Scholars of China under Grant No. 61325007, the National Natural Science Foundation of China under Grant No. 61172161.
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This article is part of the Topical Collection on Hybrid Imaging and Image Fusion.
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Kang, X., Li, S., Fang, L. et al. Pansharpening Based on Intrinsic Image Decomposition. Sens Imaging 15, 94 (2014). https://doi.org/10.1007/s11220-014-0094-8
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DOI: https://doi.org/10.1007/s11220-014-0094-8