A Multivariate Empirical Mode Decomposition Based Approach to Pansharpening

IEEE Transactions on Geoscience and Remote Sensing

Volumn 53, Issue 7, 2015, Pages 3974-3984

  Abdullah, Syed Muhammad Umer ^a   Ur Rehman, Naveed ^b   Khan, Muhammad Murtaza ^c   Mandic, Danilo P ^d  

^a Halliburton Worldwide Limited   (Pakistan)

^b Department of Electrical Computer Engineering   (Pakistan)

^c NATIONAL UNIVERSITY OF SCIENCES AND TECHNOLOGY NUST   (Pakistan)

^d IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

Image fusion; multi resolution analysis; multi variate empirical mode decomposition; pansharpening

Indexed keywords

IMAGE FUSION; IMAGE MATCHING;

COMPARATIVE ANALYSIS; EMPIRICAL MODE DECOMPOSITION; MULTI SCALE ANALYSIS; MULTICHANNEL DATA; MULTISPECTRAL IMAGES; MULTIVARIATE EMPIRICAL MODE DECOMPOSITION (MEMD); PAN-SHARPENING; SPECTRAL PERFORMANCE;

SIGNAL PROCESSING;

ALGORITHM; DATA SET; DECOMPOSITION; MULTIVARIATE ANALYSIS; SPATIAL ANALYSIS; SPECTRAL ANALYSIS;

EID: 85027958307     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2015.2388497     Document Type: Article

References (34)

1. P. Sirguey, R. Mathieu, Y. Arnaud, M. M. Khan, and J. Chanussot, "Improving MODIS spatial resolution for snow mapping using wavelet fusion and ARSIS concept," IEEE Geosci. Remote Sens. Lett., vol. 5, no. 1, pp. 78-82, Jan. 2008.
2. T. Ranchin and L. Wald, "Fusion of high spatial and spectral resolution images: The ARSIS concept and its implementation," Photogramm. Eng. Remote Sens., vol. 66, no. 1, pp. 49-61, Jan. 2000.
3. L. Zhang, H. Shen, W. Gong, and H. Zhang, "Adjustable modelbased fusion method for multispectral and panchromatic images," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 42, no. 6, pp. 1693-1704, Dec. 2012.
4. V. K. Shettigara, "A generalized component substitution technique for spatial enhancement of multispectral images using a higher resolution data set," Photogramm. Eng. Remote Sens., vol. 58, no. 5, pp. 561-567, Jan. 1992.
5. T. M. Tu, P. S. Huang, C. L. Hung and C. P. Chang, "A fast intensity-hue-saturation fusion technique with spectral adjustment for IKONOS imagery," IEEE Geosci. Remote Sens. Lett., vol. 1, no. 4, pp. 309-312, Oct. 2004.
6. S. Rahman, M. Strait, D. Merkurjev, M. Moeller, and T. Wittman, "An adaptive IHS pan-sharpening method," IEEE Geosci. Remote Sens. Lett., vol. 7, no. 4, pp. 746-750, Oct. 2010.
7. V. P. Shah, N. H. Younan, and R. L. King, "An adaptive PCA-based approach to pan-sharpening," in Proc. SPIE: Image Signal Process. Remote Sens., 2007, vol. 6748, pp. 1-9.
8. C. A. Laben and B. V. Brower, "Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening," U.S. Patent 6 011 875, Jan. 4, 2000.
9. Z. Li and H. Leung, "Fusion of multispectral and panchromatic images using a restoration-based method," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 5, pp. 1482-1491, May 2009.
10. S. Li and B. Yang, "A new pan-sharpening method using a compressed sensing technique," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 2, pp. 738-746, Feb. 2011.
11. C. Jiang, H. Zhang, H. Shen, and L. Zhang, "A practical compressed sensing-based pan-sharpening method," IEEE Geosci. Remote Sens. Lett., vol. 9, no. 4, pp. 629-633, Jul. 2012.
12. X. Zhu and R. Bamler, "A sparse image fusion algorithm with application to pan-sharpening," IEEE Trans. Geosci. Remote Sens., vol. 51, no. 5, pp. 2827-2836, 2013.
13. C. Jiang, H. Zhang, H. Shen, and L. Zhang, "Two-Step sparse coding for the pan-sharpening of remote sensing images," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 7, no. 5, pp. 1792-1805, May 2013.
14. L. Alparone et al., "Comparison of pan-sharpening algorithms: Outcome of the 2006 GRS-S data-fusion contest," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 10, pp. 3012-3021, Oct. 2007.
15. N. Huang et al., "The empirical mode decomposition and Hilbert spectrum for nonlinear and non-stationary time series analysis," Proc. R. Soc. A, vol. 454, pp. 903-995, Mar. 1998.
16. T. A. Teo and C. C. Lau, "Pyramid-based image empirical mode decomposition for the fusion of multispectral and panchromatic images," EURASIP J. Adv. Signal Process., vol. 2012, no. 4, pp. 1-12, Jan. 2012.
17. G. Rilling, P. Flandrin, P. Goncalves, and J. M. Lilly, "Bivariate empirical mode decomposition," IEEE Signal Process Lett., vol. 14, no. 12, pp. 936-939, Dec. 2007.
18. S. Chen, R. Zhang, H. Su, J. Tian and J. Xia, "SAR and multispectral image fusion using generalized IHS transform based on àtrous wavelet and EMD decompositions," IEEE Sens. J., vol. 10, no. 3, pp. 737-745, Mar. 2010.
19. D. Looney and D. P. Mandic, "Multi-Scale image fusion using complex extensions of EMD," IEEE Trans. Signal Process., vol. 57, no. 4, pp. 1626-1630, Apr. 2009.
20. N. Rehman and D. P. Mandic, "Multivariate empirical mode decomposition," Proc. R. Soc. A, vol. 466, no. 2117, pp. 1291-1302, Apr. 2010.
21. J. Nunez et al., "Multiresolution-based image fusion with additive wavelet decomposition," IEEE Trans. Geosci. Remote Sens., vol. 37, no. 3, pp. 1204-1211, May 1999.
22. B. Aiazzi, L. Alparone, S. Baronti, and A. Garzelli, "Context-driven fusion of high spatial and spectral resolution images based on oversampled multiresolution analysis," IEEE Trans. Geosci. Remote Sens., vol. 40, no. 10, pp. 2300-2312, Oct. 2002.
23. N. Rehman et al., "Image fusion using multivariate and multidimensonal EMD," IEEE Int. Conf. Image. Process., Paris, France, 2014.
24. B. Aiazzi, L. Alparone, S. Baronti, A. Garzelli and M. Selva, "MTF-tailored multiscale fusion of high-resolution MS and pan imagery," Photogramm. Eng. Remote Sens., vol. 72, no. 5, pp. 591-596, May 2006.
25. Q. Du, N. Younan, R. King, and V. Shah, "On the performance evaluation of pan-sharpening techniques," IEEE Geosci. Remote Sens. Lett, vol. 4, no. 4, pp. 518-522, Oct. 2007
26. M. Choi and R. Kim. "Fusion of multispectral and panchromatic satellite images using the curvelet transforms," IEEE Geosci. Remote Sens. Lett., vol. 2, no. 2, pp. 136-140, Apr. 2005.
27. L. Wald. "Quality of high resolution synthesized images: Is there a simple criterion?" in Proc. Int. Conf. Fusion Earth Data, 2000, pp. 99-103.
28. A. Goetz, W. Boardman and R. Yunas, "Discrimination among semi-arid landscape endmembers using the Spectral Angle Mapper (SAM) algorithm," in Proc. Summeries 3rd Annu. JPL Airborne Geosci. Workshop, 1992, pp. 147-149.
29. L. Alparone, S. Baronti, A. Garzelli, and F. Nencini, "A global quality measurement of pan-sharpened multispectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 40, no. 10, pp. 2300-2312, Mar. 2002.
30. L. Alparone, B. Aiazzi, S. Baronti, A. Garzelli and P. Nencini, "A Global Quality Measurement of Pan-sharpened Multispectral Imagery," IEEE Geosci. Remote Sens. Lett., vol. 1, no. 4, pp. 313-317, Oct. 2004.
31. Z. Wang, A. C. Bovik, H. Sheikh, and E. Simoncelli. "Image quality assessment: From error visibility to structural similarity," IEEE Trans. Image Process., vol. 13, no. 4, pp. 600-612, Apr. 2004.
32. J. Zhou, D. L. Civco, and J. A. Silander, "A wavelet transform method to merge Landsat TM and SPOT panchromatic data," Int. J. Remote Sens., vol. 19, no. 4, pp. 743-757, Mar. 1998.
33. N. Rehman, M. W. Safdar, U. Rehman and D. P. Mandic, "Dynamically-sampled bivariate empirical mode decomposition," IEEE Signal Process. Lett., vol. 21, no. 7, pp. 857-861, Jul. 2014.
34. D. Mandic, N. Rehman, Z. Wu and N. Huang, "Empirical mode decomposition based solutions for time-frequency analysis of multivariate signals," IEEE Signal Process. Mag., vol. 30, no. 6, pp. 74-85, Nov. 2013.