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Model-based variational fusion for reducing spectral distortion

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References

  1. Tu T M, Huang P S, Hung C L, et al. A fast intensityhue- saturation fusion technique with spectral adjustment for Ikonos imagery. IEEE Geosci Remote Sens Lett, 2004, 1: 309–312

    Article  Google Scholar 

  2. Tu T M, Hsu C L, Tu P Y, et al. An adjustable pan-sharpening approach for IKONOS/QuickBird/ GeoEye-1/WorldView-2 imagery. IEEE J Sel Topics Appl Earth Observ Remote Sens, 2012, 5: 125–134

    Article  Google Scholar 

  3. Khan M, Alparone L, Chanussot J. Pansharpening quality assessment using the modulation transfer functions of instruments. IEEE Trans Geosci Remote Sens, 2009, 47: 3880–3891

    Article  Google Scholar 

  4. Kallel A. MTF-adjusted pansharpening approach based on coupled multiresolution decompositions. IEEE Trans Geosci Remote Sens, 2015, 53: 3124–3145

    Article  Google Scholar 

  5. Alparone L, Aiazzi B, Baronti S, et al. Multispectral and panchromatic data fusion assessment without reference. Photogramm Eng Remote Sens, 2008, 74: 193–200

    Article  Google Scholar 

  6. Aiazzi B, Baronti S, Selva M. Improving component substitution pansharpening through multivariate regression of MS+Pan data. IEEE Trans Geosci Remote Sens, 2007, 45: 3230–3239

    Article  Google Scholar 

  7. Rahmani S, Strait M, Merkurjev D, et al. An adaptive IHS pan-sharpening method. IEEE Geosci Remote Sens Lett, 2010, 7: 746–750

    Article  Google Scholar 

  8. Palsson F, Sveinsson J, Ulfarsson M. A new pansharpening algorithm based on total variation. IEEE Geosci Remote Sens Lett, 2014, 11: 318–322

    Article  Google Scholar 

  9. Vivone G, Restaino R, Mura M D, et al. Contrast and error-based fusion schemes for multispectral image pansharpening. IEEE Geosci Remote Sens Lett, 2014, 11: 930–934

    Article  Google Scholar 

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61473310, 41174164, 41175025) and China Meteorological Administration (Grant No. GYHY201306068).

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Authors and Affiliations

  1. Institute of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing, 211101, China

    Zeming Zhou, Chaoqian Chen, Yong Meng & Biao Hu

Authors
  1. Zeming Zhou
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  2. Chaoqian Chen
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  3. Yong Meng
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  4. Biao Hu
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Corresponding author

Correspondence to Chaoqian Chen.

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The authors declare that they have no conflict of interest.

Supporting information The supporting information is available online at info.scichina.com and link.springer.com. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.

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Zhou, Z., Chen, C., Meng, Y. et al. Model-based variational fusion for reducing spectral distortion. Sci. China Inf. Sci. 61, 018102 (2018). https://doi.org/10.1007/s11432-016-9085-y

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  • DOI: https://doi.org/10.1007/s11432-016-9085-y

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