Contourlet Transform with Sparse Representation-Based Integrated Approach for Image Pansharpening

REFERENCES

• Satellite imaging corporation web page. Available: http://www.satimagingcorp.com/gallery
   Google Scholar
• I. Amro, J. Mateos, M. Vega, R. Molina and A. K. Katsaggelos. (2011). “A survey of classical methods and new trends in pansharpening of multispectral images,” EURASIP J. Adv. Signal Process. 1, pp. 79.
   Web of Science ®Google Scholar
• J. G. Liu. (2000). “Smoothing filter-based intensity modulation: A spectral preserve image fusion technique for improving spatial details,” Int J. Remote Sens. 21 (18), pp. 3461–3472.
   Web of Science ®Google Scholar
• The online resource for research in image fusion website. Available: http://www.imagefusion.org
   Google Scholar
• P. Sirguey, R. Mathieu, Y. Arnaud, M. M. Khan and J. Chanussot. (2008). “Improving MODIS spatial resolution for snow mapping using wavelet fusion and ARSIS concept,” IEEE Geosci. Remote Sens. Lett. 5 (1), pp. 78–82.
   Web of Science ®Google Scholar
• M. A. Ning, Z.-M. Zhou, P. Zhang and L.-M. Luo. (2013). “A new variational model for panchromatic and multispectral image fusion,” Acta Automat. Sinica 39 (2), pp. 179–187.
   Google Scholar
• B. Aiazzi, S. Baronti and M. Selva. (2007). “Improving component substitution pansharpening through multivariate regression of MS+Pan data,” IEEE Trans. Geosci. Remote Sens. 45 (10), pp. 3230–3239.
   Web of Science ®Google Scholar
• Q. Guo and S. Liu. (2011). “Performance analysis of multi-spectral and panchromatic image fusion techniques based on two wavelet discrete approaches,” Optik 122 (9), pp. 811–819.
   Web of Science ®Google Scholar
• W. Zhan, Y. Chen, J. Wang, J. Zhou, J. Quan, W. Liu and J. Li. (2012). “Downscaling land surface temperatures with multi-spectral and multi-resolution images,” Int. J. Appl. Earth Obs Geo-Inf. 18, pp. 23–36.
   Web of Science ®Google Scholar
• C. Pohl and J. L. V. Genderen. (1998). “Multi-sensor image fusion in remote sensing: Concepts, methods, and applications,” International J. Remote Sens. 19 (5), pp. 823–854.
   Web of Science ®Google Scholar
• T. Ranchln and L. Wald. (2000). “Fusion of high spatial and spectral resolution images: The ARSIS concept and its implementation,” Photogramm. Eng. Remote Sens. 66, pp. 49–61.
   Web of Science ®Google Scholar
• T. M. Tu, S. C. Su, H. C. Shyu and P. S. Huang. (2001). “A new look at IHS-like image fusion methods,” Inf. Fusion 2 (3), pp. 177–186.
   Google Scholar
• R. Sheida, S. Melissa, M. Daria, M. Michael and W. Todd. (2010). “An adaptive IHS Pan-sharpening method,” IEEE Geosci. Remote Sens. Lett. 3, pp. 177–186.
   Google Scholar
• V. P. Shah, N. H. Younan and R. L. King. (2008). “An efficient pan-sharpening method via a combined adaptive PCA approach and contourlets,” IEEE Trans. Geosci. Remote Sens. 46 (5), pp. 1323–1335.
   Web of Science ®Google Scholar
• S. Zebhi, M. R. Agha and M. T. Sadeghi. (2012) “Image fusion using PCA in CS domain,” Int. J. Signal Image Process. 3 (4), pp. 153.
   Google Scholar
• A. Medina, J. Marcello and F. Eugenio. (2012). “Evaluation of spatial and spectral effectiveness of pixel-level fusion techniques,” IEEE Geosci. Remote Sens. Lett. 3, pp. 432–436.
   Google Scholar
• P. J. Burt and E. H. Adelson. (1983). “The Laplacian pyramid as a compact image code,” IEEE Trans. Commun. COM-3 (4), pp. 532–540.
   Web of Science ®Google Scholar
• S. G. Mallat. (1989). “A theory for multiresolution signal decomposition: The wavelet representation,” IEEE Trans. Pattern Anal. Mach. Intell. 11 (7), pp. 674–693.
   Web of Science ®Google Scholar
• M. N. Do and M. Vetterli. (2005). “The Contourlet transform: An efficient directional multi-resolution image representation,” IEEE Trans. Image Process. 12, pp. 2091–2106.
   Web of Science ®Google Scholar
• M. Elad and M. Aharon. (2006). “Image denoising via sparse and redundant representations over learned dictionaries,” IEEE Trans. Image Process. 15 (12), pp. 3736–3745.
   PubMed Web of Science ®Google Scholar
• J. Wang, J. Peng, X. Feng, G. He, J. Wu and K. Yan. (2013). “Image fusion with nonsubsampled contourlet transform and sparse representation,” J. Electron. Imaging 22 (4), pp. 043019.
   Web of Science ®Google Scholar
• J. Cheng, H. Liu, T. Liu, F. Wang and H. Li. (2015). “Remote sensing image fusion via wavelet transform and sparse representation,” ISPRS J. Photogramm. Remote Sens. 104, pp. 158–173.
   Web of Science ®Google Scholar
• Y. Liu, S. Liu and Z. Wang. (2015). “A general framework for image fusion based on multi-scale transform and sparse representation,” Inf. Fusion 24, pp. 147–164.
   Web of Science ®Google Scholar
• S. Panchal and R. Thakker. (2016). “Improved image pansharpening technique using nonsubsampled contourlet transform with sparse representation,” J. Indian Soc. Remote Sens. pp. 1–10. doi:10.1007/s12524-016-0608-z
   Web of Science ®Google Scholar
• J. Yang, J. Wright, T. Huang and Y. Ma. (2010). “Image super-resolution via sparse representation,” IEEE Trans. Image Process. 19 (11), pp. 2861–2873.
   PubMed Web of Science ®Google Scholar
• D. N. Diana Rexiline and D. J. Anusmina, “Fusion and restoration of multi-focus image using sparse representation,” in IEEE International Conference on Advances in Engineering, Science and Management, 2012, pp. 291–296.
   Google Scholar
• Y. U. Liu and Z. Wang, “A practical pan-sharpening methods with wavelet transform and sparse representation,” in IEEE International Conference on Imaging Systems and Techniques, 2013, pp. 288–293.
   Google Scholar
• T. M. Tu, S. C. Su, H. C. Shyu and P. S. Huang. (2001). “A new look IHS-like image fusion methods,” Inf. Fusion 2 (3), pp. 177–186.
   Google Scholar
• Availabe: http://www.datatang.com/data/43234
   Google Scholar
• T. Stathaki, Image Fusion: Algorithm and Applications. Academic Press, 2011.
   Google Scholar
• J. Zhou, D. L. Civco and J. A. Silander. (1998). “A wavelet transform method to merge landsat TM and SPOT panchromatic data,” Int. J. Remote Sens. 19 (4), pp. 743–757.
   Web of Science ®Google Scholar
• L. Alparone et al. (2008). “Multispectral and panchromatic data fusion assessment without reference,” Photogramm. Engg. Remote Sens. 74 (2), pp. 193–200.
   Web of Science ®Google Scholar