Remote Sensing Image Fusion Method Based on Nonsubsampled Shearlet Transform and Sparse Representation

Sensing and Imaging

Volumn 16, Issue 1, 2015, Pages 1-18

  Moonon, Altan Ulzii ^a   Hu, Jianwen ^b   Li, Shutao ^a  

^a HUNAN UNIVERSITY   (China)

^b CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

High resolution panchromatic image; Low resolution multispectral image; Nonsubsampled shearlet transform (NSST); Remote sensing image fusion; Sparse representation

Indexed keywords

IMAGE ENHANCEMENT; IMAGE PROCESSING; IMAGE RECONSTRUCTION; INVERSE PROBLEMS; REMOTE SENSING; SPACE OPTICS;

LOW RESOLUTION MULTISPECTRAL IMAGES; PANCHROMATIC IMAGES; REMOTE SENSING IMAGES; SHEARLET TRANSFORMS; SPARSE REPRESENTATION;

IMAGE FUSION;

EID: 84948663326     PISSN: 15572064     EISSN: 15739317     Source Type: Journal    
DOI: 10.1007/s11220-015-0125-0     Document Type: Article

References (28)

1. 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.
2. Rahmani, S., Strait, M., Merkurjev, D., Moeller, M., & Wittman, T. (2010). An Adaptive IHS Pan-Sharpening method. IEEE Geoscience and Remote Sensing Letters,7(4), 746–750. doi:10.1109/lgrs.2010.2046715.
3. Shah, V. P., Younan, N. H., & King, R. L. (2007). An adaptive PCA-based approach to pan-sharpening. In Image and signal processing for remote sensing XIII, Florence, Italy, 2007 (Vol. 6748, p. 674802). International Society for Optics and Photonics. doi:10.1117/12.736674.
4. Aiazzi, B., Baronti, S., Selva, M., & Alparone, L. (2006). Enhanced Gram-Schmidt Spectral Sharpening Based on Multivariate Regression of MS and Pan Data. In 2006 IEEE international sensing symposium geoscience and remote, 31 July 2006–4 Aug 2006 (pp. 3806–3809). doi:10.1109/IGARSS.2006.975.
5. Eshtehari, A., & Ebadi, H. (2008). Image fusion of landsat ETM+ and spot satellite images using IHS, Brovey and PCA. Tehran: Toosi University of Technology.
6. Alparone, L., Wald, L., Chanussot, J., Thomas, C., Gamba, P., & Bruce, L. M. (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.
7. Garzelli, A., & Nencini, F. (2006). PAN-sharpening of very high resolution multispectral images using genetic algorithms. International Journal of Remote Sensing,27(15), 3273–3292. doi:10.1080/01431160600554991.
8. Otazu, X., Gonzalez-Audicana, M., Fors, O., & Nunez, J. (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.
9. Zheng, S., Shi, W. Z., Liu, H., & Tian, J. W. (2008). Remote sensing image fusion using multiscale mapped LS-SVM. IEEE Transactions on Geoscience and Remote Sensing,46(5), 1313–1322. doi:10.1109/Tgrs.2007.912737.
10. Shah, V. P., Younan, N. H., & King, R. (2007). Pan-sharpening via the contourlet transform. In IEEE international geoscience and remote sensing symposium, 23–28 Jul 2007 (pp. 310–313). doi:10.1109/IGARSS.2007.4422792.
11. Choi, M., Kim, R. Y., Nam, M. R., & Kim, H. O. (2005). Fusion of multispectral and panchromatic satellite images using the curvelet transform. IEEE Geoscience and Remote Sensing Letters,2(2), 136–140. doi:10.1109/lgrs.2005.845313.
12. Li, S., & Yang, B. (2011). A new pan-sharpening method using a compressed sensing technique. IEEE Transactions on Geoscience and Remote Sensing,49(2), 738–746. doi:10.1109/tgrs.2010.2067219.
13. Fasbender, D., Radoux, J., & 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.
14. Easley, G., Labate, D., & Lim, W.-Q. (2008). Sparse directional image representations using the discrete shearlet transform. Applied and Computational Harmonic Analysis,25(1), 25–46. doi:10.1016/j.acha.2007.09.003.
15. Elad, M., & Aharon, M. (2006). Image denoising via sparse and redundant representations over learned dictionaries. IEEE Transactions on Image Processing,15(12), 3736–3745. doi:10.1109/TIP.2006.881969.
16. Choi, M. J., Kim, H. C., Cho, N. I., & Kim, H. O. (2008). An improved intensity–hue–saturation method for IKONOS image fusion. International Journal of Remote Sensing (in pre-print).
17. Tu, T. M., Huang, P. S., Hung, C. L., & Chang, C. P. (2004). A fast IHS fusion technique with spectral adjustment for IKONOS imagery. IEEE Geoscience and Remote Sensing Letters,1(4), 309–312. doi:10.1109/lgrs.2004.834804.
18. Guo, K., & Labate, D. (2007). Optimally sparse multidimensional representation using shearlets. SIAM Journal on Mathematical Analysis,39(1), 298–318. doi:10.1137/060649781.
19. Davenport, M. A., Duarte, M. F., Eldar, Y. C., & Kutyniok, G. (2012). Introduction to compressed sensing. In Y. C. Eldar, & G. Kutyniok (Eds.), Compressed sensing: Theory and applications. Cambridge, UK: Cambridge University Press.
20. Pati, Y. C., Rezaiifar, R., & Krishnaprasad, P. S. (1993). Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition. In Proceedings of 27th Asilomar conference on signals, systems and computers 1–3 Nov 1993 (Vol. 1, pp. 40–44), doi:10.1109/ACSSC.1993.342465.
21. Chen, S. S., Donoho, D. L., & Saunders, M. A. (1998). atomic decomposition by basis pursuit. SIAM Journal on Scientific Computing,20(1), 33–61. doi:10.1137/s1064827596304010.
22. Starck, J. L., Elad, M., & Donoho, D. L. (2005). Image decomposition via the combination of sparse representations and a variational approach. IEEE Transactions on Image Processing,14(10), 1570–1582. doi:10.1109/TIP.2005.852206.
23. Rubinstein, R., Bruckstein, A. M., & Elad, M. (2010). Dictionaries for sparse representation modeling. Proceedings of the IEEE,98(6), 1045–1057. doi:10.1109/jproc.2010.2040551.
24. Engan, K., Aase, S. O., & Hakon Husoy, J. (1999). Method of optimal directions for frame design. In IEEE international conference on acoustics, speech, and signal processing 1999 (Vol. 5, pp. 2443–2446). doi:10.1109/ICASSP.1999.760624.
25. Aharon, M., Elad, M., & Bruckstein, A. (2006). K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation. IEEE Transactions on Signal Processing,54(11), 4311–4322. doi:10.1109/tsp.2006.881199.
26. Wald, L., Ranchin, T., & Mangolini, M. (1997). Fusion of satellite images of different spatial resolutions: Assessing the quality of resulting images. Photogrammetric Engineering and Remote Sensing,63(6), 691–699.
27. Khan, M. M., Alparone, L., & Chanussot, J. (2009). Pansharpening quality assessment using the modulation transfer functions of instruments. IEEE Transactions on Geoscience and Remote Sensing,47(11), 3880–3891. doi:10.1109/tgrs.2009.2029094.
28. Alparone, L., Baronti, S., Garzelli, A., & Nencini, F. (2004). A global quality measurement of pan-sharpened multispectral imagery. IEEE Geoscience and Remote Sensing Letters,1(4), 313–317. doi:10.1109/lgrs.2004.836784.