Hyperspectral super-resolution by coupled spectral unmixing

Proceedings of the IEEE International Conference on Computer Vision

Volumn 2015 International Conference on Computer Vision, ICCV 2015, Issue , 2015, Pages 3586-3594

  Lanaras, Charis ^a   Baltsavias, Emmanuel ^a   Schindler, Konrad ^a  

^a ETH ZURICH   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; MIXING; SPECTRAL RESOLUTION; SPECTROSCOPY;

ELECTROMAGNETIC SPECTRA; HIGH RESOLUTION IMAGE; HIGH SPECTRAL RESOLUTION; HYPER-SPECTRAL CAMERAS; HYPER-SPECTRAL IMAGES; MIXING COEFFICIENT; REFLECTANCE SPECTRUM; SPATIAL RESOLUTION;

OPTICAL RESOLVING POWER;

EID: 84964383694     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2015.409     Document Type: Conference Paper

References (31)

1. N. Akhtar, F. Shafait, and A. Mian. Sparse spatio-spectral representation for hyperspectral image super-resolution. In Computer Vision-ECCV 2014, pages 63-78. Springer, 2014.
2. N. Akhtar, F. Shafait, and A. Mian. Bayesian sparse representation for hyperspectral image super resolution. In IEEE Computer Vision and Pattern Recognition (CVPR), pages 3631-3640, 2015.
3. L. Alparone, L. Wald, J. Chanussot, C. Thomas, P. Gamba, and L. M. Bruce. Comparison of pansharpening algorithms: Outcome of the 2006 GRS-S data-fusion contest. IEEE Transactions on Geoscience and Remote Sensing, 45(10):3012-3021, 2007.
4. J. M. Bioucas-Dias. A variable splitting augmented lagrangian approach to linear spectral unmixing. In FirstWorkshop on Hyperspectral Image and Signal Processing: Evolu-tion in Remote Sensing (WHISPERS'09), pages 1-4. IEEE, 2009.
5. J. M. Bioucas-Dias and J. M. Nascimento. Hyperspectral subspace identification. IEEE Transactions on Geoscience and Remote Sensing, 46(8):2435-2445, 2008.
6. J. M. Bioucas-Dias, A. Plaza, G. Camps-Valls, P. Scheunders, N. M. Nasrabadi, and J. Chanussot. Hyperspectral remote sensing data analysis and future challenges. IEEE, Geoscience and Remote Sensing Magazine, 1(2):6-36, 2013.
7. J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot. Hyperspectral unmixing overview: Geometrical, statistical, and sparse regressionbased approaches. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(2):354-379, 2012.
8. J. Bolte, S. Sabach, and M. Teboulle. Proximal alternating linearized minimization for nonconvex and nonsmooth problems. Mathematical Programming, 146(1-2):459-494, 2014.
9. A. Chakrabarti and T. Zickler. Statistics of Real-World Hyperspectral Images. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages 193-200, 2011.
10. L. Condat. Fast projection onto the simplex and the l1 ball, 2014. [Online] http://hal. univ-grenoble-alpes. fr/hal-01056171/.
11. Y. Gu, Y. Zhang, and J. Zhang. Integration of spatial-spectral information for resolution enhancement in hyperspectral images. IEEE Transactions on Geoscience and Remote Sensing, 46(5):1347-1358, 2008.
12. R. C. Hardie, M. T. Eismann, and G. L. Wilson. Map estimation for hyperspectral image resolution enhancement using an auxiliary sensor. IEEE Transactions on Image Processing, 13(9):1174-1184, 2004.
13. B. Huang, H. Song, H. Cui, J. Peng, and Z. Xu. Spatial and spectral image fusion using sparse matrix factorization. IEEE Transactions on Geoscience and Remote Sensing, 52(3):1693-1704, 2014.
14. F. H. Imai and R. S. Berns. High-resolution multi-spectral image archives: A hybrid approach. In 6th Color and Imaging Conference, volume 1998, pages 224-227. Society for Imaging Science and Technology, 1998.
15. T. Kasetkasem, M. K. Arora, and P. K. Varshney. Superresolution land cover mapping using a markov random field based approach. Remote Sensing of Environment, 96(3):302-314, 2005.
16. R. Kawakami, J. Wright, Y.-W. Tai, Y. Matsushita, M. Ben-Ezra, and K. Ikeuchi. High-resolution hyperspectral imaging via matrix factorization. In IEEE Computer Vision and Pattern Recognition (CVPR), pages 2329-2336. IEEE, 2011.
17. N. Keshava and J. F. Mustard. Spectral unmixing. IEEE Signal Processing Magazine, 19(1):44-57, 2002.
18. S. J. Kim, F. Deng, and M. S. Brown. Visual enhancement of old documents with hyperspectral imaging. Pattern Recognition, 44(7):1461-1469, 2011.
19. Z. Pan, G. Healey, M. Prasad, and B. Tromberg. Face recognition in hyperspectral images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(12):1552-1560, 2003.
20. C. Pohl and J. L. V. Genderen. Review article multisensor image fusion in remote sensing: Concepts, methods and applications. International Journal of Remote Sensing, 19(5):823-854, 1998.
21. M. Simoes, J. Bioucas-Dias, L. Almeida, and J. Chanussot. A convex formulation for hyperspectral image superresolution via subspace-based regularization. IEEE Transactions on Geoscience and Remote Sensing, 53(6):3373-3388, 2015.
22. Y. Tarabalka, J. Chanussot, and J. A. Benediktsson. Segmentation and classification of hyperspectral images using watershed transformation. Pattern Recognition, 43(7):2367-2379, 2010.
23. H. Van Nguyen, A. Banerjee, and R. Chellappa. Tracking via object reflectance using a hyperspectral video camera. In IEEE Computer Vision and Pattern Recognition Workshops (CVPRW), pages 44-51. IEEE, 2010.
24. Z. Wang, D. Ziou, C. Armenakis, D. Li, and Q. Li. A comparative analysis of image fusion methods. IEEE Transactions on Geoscience and Remote Sensing, 43(6):1391-1402, 2005.
25. Q. Wei, N. Dobigeon, and J.-Y. Tourneret. Bayesian fusion of hyperspectral and multispectral images. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 3176-3180. IEEE, 2014.
26. D. Wu and D.-W. Sun. Advanced applications of hyperspectral imaging technology for food quality and safety analysis and assessment: A reviewpart i: Fundamentals. Innovative Food Science & Emerging Technologies, 19:1-14, 2013.
27. E. Wycoff, T.-H. Chan, K. Jia, W.-K. Ma, and Y. Ma. A non-negative sparse promoting algorithm for high resolution hyperspectral imaging. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 1409-1413. IEEE, 2013.
28. F. Yasuma, T. Mitsunaga, D. Iso, and S. Nayar. Generalized Assorted Pixel Camera: Post-Capture Control of Resolution, Dynamic Range and Spectrum. Technical report, Nov. 2008.
29. N. Yokoya, T. Yairi, and A. Iwasaki. Coupled nonnegative matrix factorization unmixing for hyperspectral and multispectral data fusion. IEEE Transactions on Geoscience and Remote Sensing, 50(2):528-537, 2012.
30. R. H. Yuhas, A. F. Goetz, and J. W. Boardman. Discrimination among semi-arid landscape endmembers using the spectral angle mapper (SAM) algorithm. In Summaries of the Third Annual JPL Airborne Geoscience Workshop, pages 147-149, 1992.
31. H. Zhang, L. Zhang, and H. Shen. A super-resolution reconstruction algorithm for hyperspectral images. Signal Processing, 92(9):2082-2096, 2012.