1,391
Views
30
CrossRef citations to date
0
Altmetric
Review Article

Structuring contemporary remote sensing image fusion

&
Pages 3-21 | Received 22 Nov 2014, Accepted 10 Dec 2014, Published online: 16 Feb 2015

References

  • Abdikan, S., et al., 2012. A comparative data-fusion analysis of multi-sensor satellite images. International Journal of Digital Earth, 7 (8), 671–687.
  • Aiazzi, B., et al., 2003. An MTF-based spectral distortion minimizing model for pan-sharpening of very high resolution multispectral images of urban areas. In: 2nd GRSS/ISPRS joint workshop on remote sensing and data fusion over urban areas, 22–23 May, Berlin, 90–94.
  • Aiazzi, B., et al., 2006. Enhanced Gram-schmidt spectral sharpening based on multivariate regression of MS and pan data. In: IEEE international conference on geoscience and remote sensing symposium, IGARSS 2006, 31 July–4 August, Denver, CO, 3806–3809.
  • Aiazzi, B., et al., 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:10.1109/TGRS.2002.803623
  • Aiazzi, B., et al., 2009. A comparison between global and context-adaptive pansharpening of multispectral images. IEEE Geoscience and Remote Sensing Letters, 6 (2), 302–306. doi:10.1109/LGRS.2008.2012003
  • Alparone, L., et al., 2004. Landsat ETM+ and SAR image fusion based on generalized intensity modulation. IEEE Transactions on Geoscience and Remote Sensing, 42 (12), 2832–2839. doi:10.1109/TGRS.2004.838344
  • Alparone, L., et al., 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:10.1109/TGRS.2007.904923
  • Amolins, K., Zhang, Y., and Dare, P., 2007. Wavelet based image fusion techniques — an introduction, review and comparison. ISPRS Journal of Photogrammetry and Remote Sensing, 62 (4), 249–263. doi:10.1016/j.isprsjprs.2007.05.009
  • Ashraf, S., Brabyn, L., and Hicks, B.J., 2013. Alternative solutions for determining the spectral band weights for the subtractive resolution merge technique. International Journal of Image and Data Fusion, 4 (2), 105–125. doi:10.1080/19479832.2011.607473
  • Ballester, C., et al., 2006. A variational model for P+XS image fusion. International Journal of Computer Vision, 69 (1), 43–58. doi:10.1007/s11263-006-6852-x
  • Berger, C., 2010. Fusion of high resolution SAR data and multispectral imagery at pixel level – a comprehensive evaluation. Thesis (MSc). Friedrich-Schiller-University Jena.
  • Berger, C., et al., 2013. Multi-modal and multi-temporal data fusion: outcome of the 2012 GRSS data fusion contest. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6 (3), 1324–1340. doi:10.1109/JSTARS.2013.2245860
  • Byun, Y., Choi, J., and Han, Y., 2013. An area-based image fusion scheme for the integration of SAR and optical satellite imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6 (5), 2212–2220. doi:10.1109/JSTARS.2013.2272773
  • Cakir, H.I. and Khorram, S., 2008. Pixel level fusion of panchromatic and multispectral images based on correspondence analysis. Photogrammetric Engineering and Remote Sensing, 74 (2), 183–192. doi:10.14358/PERS.74.2.183
  • Chavez, P.S., Sides, S.C., and Anderson, I.A., 1991. Comparison of three different methods to merge multiresolution and multispectral data: Landsat TM and SPOT panchromatic. Photogrammetric Engineering and Remote Sensing, 57 (3), 295–303.
  • Chen, C.-M., Hepner, G.F., and Forster, R.R., 2003. Fusion of hyperspectral and radar data using the IHS transformation to enhance urban surface features. ISPRS Journal of Photogrammetry and Remote Sensing, 58 (1–2), 19–30. doi:10.1016/S0924-2716(03)00014-5
  • Chen, S., et al., 2012. Scaling between Landsat-7 and SAR images based on ensemble empirical mode decomposition. International Journal of Remote Sensing, 33 (3), 826–835. doi:10.1080/01431161.2011.577833
  • Chiang, J.-L., 2014. Knowledge-based principal component analysis for image fusion. Applied Mathematics & Information Sciences, 8 (1L), 223–230. doi:10.12785/amis/081L28
  • Chibani, Y., 2007. Integration of panchromatic and SAR features into multispectral SPOT images using the ‘à trous’ wavelet decomposition. International Journal of Remote Sensing, 28 (10), 2295–2307. doi:10.1080/01431160600606874
  • Chibani, Y. and Houacine, A., 2002. The joint use of IHS transform and redundant wavelet decomposition for fusing multispectral and panchromatic images. International Journal of Remote Sensing, 23 (18), 3821–3833. doi:10.1080/01431160110107626
  • Cho, K., et al., 2013. Resilience against disasters using remote sensing and geoinformation technologies for rapid mapping and information dissemination (RAPIDMAP). In: 34th Asian conference on remote sensing 2013, ACRS 2013, 20–24 October, Bali. Asian Association on Remote Sensing, 3826–3833.
  • Choi, J., et al., 2013. Hybrid pansharpening algorithm for high spatial resolution satellite imagery to improve spatial quality. IEEE Geoscience and Remote Sensing Letters, 10 (3), 490–494. doi:10.1109/LGRS.2012.2210857
  • Choi, M., 2006. A new intensity-hue-saturation fusion approach to image fusion with a tradeoff parameter. IEEE Transactions on Geoscience and Remote Sensing, 44 (6), 1672–1682. doi:10.1109/TGRS.2006.869923
  • Delalieux, S., et al., 2014. Unmixing-based fusion of hyperspatial and hyperspectral airborne imagery for early detection of vegetation stress. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7 (6), 2571–2582. doi:10.1109/JSTARS.2014.2330352
  • Deng, J.S., et al., 2008. PCA-based land-use change detection and analysis using multitemporal and multisensor satellite data. International Journal of Remote Sensing, 29 (16), 4823–4838. doi:10.1080/01431160801950162
  • Duran, J., et al., 2014. A nonlocal variational model for pansharpening image fusion. SIAM Journal on Imaging Sciences, 7 (2), 761–796. doi:10.1137/130928625
  • Ehlers, M., et al., 2010a. Multi-sensor image fusion for pansharpening in remote sensing. International Journal of Image and Data Fusion, 1 (1), 25–45. doi:10.1080/19479830903561985
  • Ehlers, M., et al., 2010b. Multi-sensor image fusion for pansharpening in remote sensing. International Journal of Image and Data Fusion, 1 (1), 25–45. doi:10.1080/19479830903561985
  • Fasbender, D., Radoux, J., and Bogaert, P., 2008. Bayesian data fusion for adaptable image pansharpening. IEEE Transactions on Geoscience and Remote Sensing, 46 (6), 1847–1857. doi:10.1109/TGRS.2008.917131
  • Gao, F., et al., 2006. On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance. IEEE Transactions on Geoscience and Remote Sensing, 44 (8), 2207–2218. doi:10.1109/TGRS.2006.872081
  • Garzelli, A. and Nencini, F., 2005. Interband structure modeling for Pan-sharpening of very high-resolution multispectral images. Information Fusion, 6 (3), 213–224. doi:10.1016/j.inffus.2004.06.008
  • Gevaert, C., 2014. Combing hyperspectral UAV and multispectral Formosat-2 imagery for precision agriculture applications. Thesis (MSc). Lund University.
  • Ha, W., Gowda, P.H., and Howell, T.A., 2013. A review of potential image fusion methods for remote sensing-based irrigation management: part II. Irrigation Science, 31 (4), 851–869. doi:10.1007/s00271-012-0340-6
  • Hilker, T., et al., 2009. A new data fusion model for high spatial- and temporal-resolution mapping of forest disturbance based on Landsat and MODIS. Remote Sensing of Environment, 113 (8), 1613–1627. doi:10.1016/j.rse.2009.03.007
  • 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 & Remote Sensing, 75 (10), 1213–1223. doi:10.14358/PERS.75.10.1213
  • Huang, B., et al., 2013. Unified fusion of remote-sensing imagery: generating simultaneously high-resolution synthetic spatial–temporal–spectral earth observations. Remote Sensing Letters, 4 (6), 561–569. doi:10.1080/2150704X.2013.769283
  • Kang, X., Li, S., and Benediktsson, J.A., 2014. Pansharpening with matting model. IEEE Transactions on Geoscience and Remote Sensing, 52 (8), 5088–5099. doi:10.1109/TGRS.2013.2286827
  • Khan, M.M., et al., 2008. Indusion: fusion of multispectral and panchromatic images using the induction scaling technique. IEEE Geoscience and Remote Sensing Letters, 5 (1), 98–102. doi:10.1109/LGRS.2007.909934
  • Klonus, S. 2008. Comparison of pansharpening algorithms for combining radar and multispectral data. In: XXI ISPRS congress, 3–11 July, Beijing. ISPRS, 189–194.
  • Klonus, S. and Ehlers, M., 2007. Image fusion using the Ehlers spectral characteristics preservation algorithm. GIScience & Remote Sensing, 44 (2), 93–116. doi:10.2747/1548-1603.44.2.93
  • Laben, C.A., Bernard, V., and Brower, W., 2000. Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening. US & International application 6,011,875.
  • Lang, J. and Hao, Z., 2014. Novel image fusion method based on adaptive pulse coupled neural network and discrete multi-parameter fractional random transform. Optics and Lasers in Engineering, 52 (1), 91–98. doi:10.1016/j.optlaseng.2013.07.005
  • Leung, Y., Liu, J., and Zhang, J., 2014. An improved adaptive intensity–hue–saturation method for the fusion of remote sensing images. IEEE Geoscience and Remote Sensing Letters, 11 (5), 985–989. doi:10.1109/LGRS.2013.2284282
  • Li, S., Yin, H., and Fang, L., 2013. Remote sensing image fusion via sparse representations over learned dictionaries. IEEE Transactions on Geoscience and Remote Sensing, 51 (9), 4779–4789. doi:10.1109/TGRS.2012.2230332
  • 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. doi:10.1080/014311600750037499
  • Malpica, J.A., 2007. Hue adjustment to IHS Pan-Sharpened IKONOS imagery for vegetation enhancement. IEEE Geoscience and Remote Sensing Letters, 4 (1), 27–31. doi:10.1109/LGRS.2006.883523
  • Metwalli, M.R., et al., 2014. Efficient pan-sharpening of satellite images with the contourlet transform. International Journal of Remote Sensing, 35 (5), 1979–2002. doi:10.1080/01431161.2013.873832
  • Nunez, J., et al., 1999. Multiresolution-based image fusion with additive wavelet decomposition. IEEE Transactions on Geoscience and Remote Sensing, 37 (3), 1204–1211. doi:10.1109/36.763274
  • Otazu, X., et al., 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. doi:10.1109/TGRS.2005.856106
  • Padwick, C., et al., Worldview-2 Pan-sharpening. In: ASPRS Annual Conference, 2010 San Diego, CA.
  • Palsson, F., Sveinsson, J.R., and Ulfarsson, M.O., 2014. A new pansharpening algorithm based on total variation. IEEE Geoscience and Remote Sensing Letters, 11 (1), 318–322. doi:10.1109/LGRS.2013.2257669
  • Palubinskas, G., 2013. Fast, simple, and good pan-sharpening method. Journal of Applied Remote Sensing, 7 (1), 073526. doi:10.1117/1.JRS.7.073526
  • Palubinskas, G. and Reinartz, P. 2011. Multi-resolution, multi-sensor image fusion: general fusion framework. In: 2011 Joint urban remote sensing event (JURSE), 11–13 April, Munich. IEEE, 313–316.
  • Palubinskas, G., Reinartz, P., and Bamler, R., 2010. Image acquisition geometry analysis for the fusion of optical and radar remote sensing data. International Journal of Image and Data Fusion, 1 (3), 271–282. doi:10.1080/19479832.2010.484152
  • Pohl, C. and Van Genderen, J., 1998. Review article multisensor image fusion in remote sensing: concepts, methods and applications. International Journal of Remote Sensing, 19 (5), 823–854. doi:10.1080/014311698215748
  • Pohl, C. and Van Genderen, J., 2014. Remote sensing image fusion: an update in the context of Digital Earth. International Journal of Digital Earth, 7 (2), 158–172. doi:10.1080/17538947.2013.869266
  • Rahmani, S., et al., 2010. An adaptive IHS Pan-Sharpening method. IEEE Geoscience and Remote Sensing Letters, 7 (4), 746–750. doi:10.1109/LGRS.2010.2046715
  • Ranchin, T., et al., 2003. Image fusion—the ARSIS concept and some successful implementation schemes. ISPRS Journal of Photogrammetry and Remote Sensing, 58, 4–18. doi:10.1016/S0924-2716(03)00013-3
  • Ranchin, T. and Wald, L., 2000. Fusion of high spatial and spectral resolution images: the ARSlS concept and its implementation. Photogrammetric Engineering & Remote Sensing, 66 (1), 4–18.
  • Rokni, K., et al., 2015. A new approach for surface water change detection: integration of pixel level image fusion and image classification techniques. International Journal of Applied Earth Observation and Geoinformation, 34, 226–234. doi:10.1016/j.jag.2014.08.014
  • Rong, K., et al., 2014. Pansharpening by exploiting sharpness of the spatial structure. International Journal of Remote Sensing, 35 (18), 6662–6673. doi:10.1080/2150704X.2014.960607
  • Schowengerdt, R.A., 1980. Reconstruction of multi-spatial, multi-spectral image data using spatial frequency content. Photogrammetric Engineering & Remote Sensing, 45 (10), 1325–1334.
  • Schowengerdt, R.A., 2007. Chapter 8 – Image registration and fusion. In: R.A. Schowengerdt, ed. Remote sensing. 3rd ed. Burlington, VT: Academic Press, 355–385.
  • Shah, V.P., Younan, N.H., and King, R.L., 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:10.1109/TGRS.2008.916211
  • Siddiqui, Y., 2003. The modified IHS method for fusing satellite imagery. In: ASPRS Annual Conference. Anchorage, Alaska.
  • Su, Y., Lee, C.H., and Tu, T.M., 2013. A multi-optional adjustable IHS-BT approach for high resolution optical and SAR image fusion. Chung Cheng Ling Hsueh Pao/Journal of Chung Cheng Institute of Technology, 42 (1), 119–128.
  • Thomas, C., et al., 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. doi:10.1109/TGRS.2007.912448
  • Tu, T.-M., et al., 2007. Best tradeoff for high-resolution image fusion to preserve spatial details and minimize color distortion. IEEE Geoscience and Remote Sensing Letters, 4 (2), 302–306. doi:10.1109/LGRS.2007.894143
  • Tu, T.-M., et al., 2004. A fast intensity–hue–saturation fusion technique with spectral adjustment for IKONOS imagery. IEEE Geoscience and Remote Sensing Letters, 1 (4), 309–312. doi:10.1109/LGRS.2004.834804
  • Tu, T.-M., et al., 2001. A new look at IHS-like image fusion methods. Information Fusion, 2 (3), 177–186. doi:10.1016/S1566-2535(01)00036-7
  • Vrabel, J., 2000. Multispectral imagery advanced band sharpening study. Photogrammetric Engineering & Remote Sensing, 66 (1), 73–79.
  • Wang, Z., et al., 2005. A comparative analysis of image fusion methods. IEEE Transactions on Geoscience and Remote Sensing, 43 (6), 1391–1402. doi:10.1109/TGRS.2005.846874
  • Xiao, M. and He, Z. 2013. Remote sensing image fusion based on Gaussian mixture model and multiresolution analysis. 89210Q-89210Q-89218.
  • Xu, Q., et al., 2014a. High-fidelity component substitution pansharpening by the fitting of substitution data. IEEE Transactions on Geoscience and Remote Sensing, 52 (11), 7380–7392. doi:10.1109/TGRS.2014.2311815
  • Xu, Q., Zhang, Y., and Li, B., 2014b. Recent advances in pansharpening and key problems in applications. International Journal of Image and Data Fusion, 5 (3), 175–195. doi:10.1080/19479832.2014.889227
  • Xu, Q., et al., 2015. Pansharpening using regression of classified MS and pan images to reduce color distortion. IEEE Geoscience and Remote Sensing Letters, 12 (1), 28–32. doi:10.1109/LGRS.2014.2324817
  • Yang, J. and Zhang, J., 2014. Pansharpening: from a generalised model perspective. International Journal of Image and Data Fusion, 1–15. doi:10.1080/19479832.2014.936528
  • Yang, X.-H. and Jiao, L.-C., 2008. Fusion algorithm for remote sensing images based on nonsubsampled contourlet transform. Acta Automatica Sinica, 34 (3), 274–281. doi:10.3724/SP.J.1004.2008.00274
  • Yin, N. and Jiang, Q.-G. 2013. Feasibility of multispectral and synthetic aperture radar image fusion. In: 6th international congress on image and signal processing (CISP), 16–18 December. Hangzhou: IEEE, 835–839.
  • Yonghong, J. and Blum, R.S., 2008. A fusion method of SAR and optical images for urban object extraction. In: ISPRS ed. ISPRS congress. Beijing: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 1–4.
  • Zhang, J., 2010. Multi-source remote sensing data fusion: status and trends. International Journal of Image and Data Fusion, 1 (1), 5–24. doi:10.1080/19479830903561035
  • Zhang, J., et al., 2010. Block-regression based fusion of optical and SAR imagery for feature enhancement. International Journal of Remote Sensing, 31 (9), 2325–2345. doi:10.1080/01431160902980324
  • Zhang, J., Zhang, Y., and Chen, H., 2011. Fusion of multispectral and panchromatic images based on transferable parameters. International Journal of Image and Data Fusion, 2 (3), 191–215. doi:10.1080/19479832.2010.542189
  • Zhang, L., et al., 2013a. Maximum local energy method and sum modified Laplacian for remote image fusion based on beyond wavelet transform. International Journal on Applied Mathematics & Information Sciences, 7 (1), 149S–156S.
  • Zhang, Y., 2004. Understanding image fusion. Photogrammetric Engineering & Remote Sensing, 70 (6), 657–661.
  • Zhang, Y., 2012. Wavelet-based Bayesian fusion of multispectral and hyperspectral images using Gaussian scale mixture model. International Journal of Image and Data Fusion, 3 (1), 23–37. doi:10.1080/19479832.2010.551522
  • Zhang, Y. and Hong, G., 2005. An IHS and wavelet integrated approach to improve pan-sharpening visual quality of natural colour IKONOS and QuickBird images. Information Fusion, 6 (3), 225–234. doi:10.1016/j.inffus.2004.06.009
  • Zhang, Y. and Mishra, R.K., 2014. From UNB PanSharp to Fuze Go – the success behind the pan-sharpening algorithm. International Journal of Image and Data Fusion, 5 (1), 39–53. doi:10.1080/19479832.2013.848475
  • Zhang, Z., Shi, Z., and An, Z., 2013b. Hyperspectral and panchromatic image fusion using unmixing-based constrained nonnegative matrix factorization. OPTIK – International Journal for Light and Electron Optics, 124 (13), 1601–1608. doi:10.1016/j.ijleo.2012.04.022
  • Zhou, X., et al., 2014. A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation. ISPRS Journal of Photogrammetry and Remote Sensing, 88, 16–27. doi:10.1016/j.isprsjprs.2013.11.011

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.