Comparison of different pan-sharpening methods for spectral characteristic preservation: Multi-temporal CARTOSAT-1 and IRS-P6 LISS-IV imagery

International Journal of Remote Sensing

Volumn 33, Issue 18, 2012, Pages 5629-5643

  Jalan, Seema ^a   Sokhi, Baldeo Singh ^b  

^a UNIVERSITY OF RAJASTHAN   (India)

^b INDIAN INSTITUTE OF REMOTE SENSING   (India)

Author keywords

[No Author keywords available]

Indexed keywords

HIGH PASS FILTERS; PHOTOMAPPING; REMOTE SENSING; SENSOR DATA FUSION; SPECTRAL RESOLUTION;

DIFFERENT RESOLUTIONS; HIGH SPECTRAL RESOLUTION; IMAGE FUSION ALGORITHMS; IMAGE FUSION TECHNIQUES; INDIAN REMOTE SENSING SATELLITE; MAPPING APPLICATIONS; SPECTRAL CHARACTERISTICS; SPECTRAL DISTORTIONS;

IMAGE FUSION;

ALGORITHM; CARTOSAT-1; COMPARATIVE STUDY; IMAGE ANALYSIS; IRS (SATELLITE); LANDSCAPE; LISS; MAPPING METHOD; REMOTE SENSING; SATELLITE IMAGERY; SATELLITE SENSOR; SPATIAL RESOLUTION; SPECTRAL RESOLUTION; URBAN AREA;

EID: 84859771694     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2012.666811     Document Type: Article

References (25)

1. Chavez, P.S., Sides, S.C. and Anderson, J.A. 1991. Comparison of three different methods to merge multiresolution and multispectral data: Landsat TM and SPOT panchromatic. Photogrammetric Engineering and Remote Sensing, 55: 327-331.
2. Ehlers, M. 2004. "Spectral characteristics preserving image fusion based on Fourier domain filtering". In Proceedings of the SPIE, Remote Sensing for Environmental Monitoring, GIS Applications and Geology, Edited by: Ehlers, M., Posa, F., Kaufmann, H.J., Michel, U. and De Carolis, G. Vol. 5574, 1-13. Bellingham, WA: SPIE.
3. Ehlers, M. 2007. "New developments and trends for urban remote sensing". In Urban Remote Sensing, Edited by: Weng, Q. and Quattrochi, D.A. 357-374. London: Taylor and Francis.
4. Ehlers, M. Multi-image fusion in remote sensing: spatial enhancement vs. spectral characteristics preservation. Proceedings of 4th International Symposium (Part II), ISVC 2008. December1-32008, Las Vegas, NV. pp.75-84. Berlin: Springer.
5. Ehlers, M., Klonus, S. and Astrand, P.J. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. July3-112008, China. Vol. 37, pp.499-505. Beijing: International Society for Photogrammetry and Remote Sensing.
6. Fasbender, D., Radoux, J. and Bogaert, P. 2008. Bayesian data fusion for adaptable image pansharpening. IEEE Transactions on Geoscience and Remote Sensing, 46: 1847-1856.
7. Gangkofner, U.G., Pradhan, P.S. and Holcomb, D.W. 2008. Optimizing the high-pass filter addition technique for image fusion. Photogrammetric Engineering and Remote Sensing, 74: 1107-1118.
8. Gupta, K. and Jain, S. 2005. Enhanced capabilities of IRS P6 LISS IV sensor for urban mapping. Current Sciences, 89: 1805-1812.
9. Klonus, S. And Ehlers,M., 2009, Performance of evaluation methods in image fusion. In 12th International Conference on Image Fusion, 6-9 July 2009, Seattle, WA, pp. 1409-1416. http://isif.org/fusion/proceedings/fusion09CD/data/papers/0136.pdf (Accessed: 1 December 2010).
10. Laben, C.A., Bernard, V. and Brower, W. Process for enhancing the spatial resolution of multispectral imagery using pan sharpening. US Patent 6,011,875. 2000.
11. Li, C., Liu, L., Wang, J., Zhao, C. and Wang, R. Proceedings of Geoscience and Remote Sensing Symposium, IGARSS'04. Comparison of two methods of the fusion of remote sensing images with fidelity of spectral information. September20-242004. Vol. 4, pp.2561-2564. New York: IEEE.
12. Li, C. and Xu, D., 2009, Study of methods of fusion and classification using SPOT 5 image of Zhongshan cemetery. In Joint Urban Remote Sensing Event, 20-22 May 2009, Shanghai, pp. 1-5. http://www.ieeexplore.ieee.org (Accessed: 1 December 2010).
13. Li, C., Yang, X., Chu, B., Lu, W. And Pang, L., 2010, A new image fusion quality assessment method based on Contourlet and SSIM. In 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT), 9-11 July 2010, Chengdu, China (New York: IEEE), 5, pp. 246-249. http://www.ieeexplore.ieee.org (Accessed: 1 December 2010).
14. Li, S. And Li, Z., 2010, Effects of image fusion algorithms on classification accuracy. In 18th International Conference on Geoinformatics, 18-20 June 2010, Beijing, China (New York: IEEE),pp. 1-6 http://www.ieeexplore.ieee.org (Accessed: 1 December 2010).
15. Munechika, C.K., Warnick, J.S., Salvaggio, C. and Schott, J.R. 1993. Resolution enhancement of multispectral image data to improve classification accuracy. Photogrammetric Engineering and Remote Sensing, 59: 67-72.
16. Pohl, C. and Genderen, J.L.V. 1998. Multisensor image fusion in remote sensing: concepts, methods and applications. International Journal of Remote Sensing, 19: 823-854.
17. Pradhan, P., King, R., Younan, N.H. and Holcomb, D.W. 2006. The effect of decomposition levels in wavelet-based fusion for multi-resolution and multi-sensor images. IEEE Transactions on Geoscience and Remote Sensing, 44: 3674-3686.
18. Schowengerdt, R.A. 1982. Reconstruction of multispatial, multispectral image data using spatial frequency content. Photogrammetric Engineering and Remote Sensing, 46: 1325-1334.
19. Švab, A. and Oštir, K. 2006. High resolution image fusion: methods to preserve spectral and spatial resolution. Photogrammetric Engineering and Remote Sensing, 72: 565-572.
20. Tao, J., Dabin, J. And Jinfang, H., 2010, Comparison study of different fusion methods based on remote sensing image. In 3rd International Congress on Image and Signal Processing (CISP), 16-18 October 2010, Yantai, China (New York: IEEE), 5, pp. 2149-2153. http://www.ieeexplore/ieee.org (Accessed: 1 December 2010).
21. Thomas, C. and Wald, L. 2006. "Comparing distances for quality assessment of fused images". In New Developments and Challenges in Remote Sensing, Edited by: Bochenek, Z. 101-111. Rotterdam: Mill Press.
22. Wald, L., Ranchin, T. and Mangolini, M. 1997. Fusion of satellite images of different spatial resolutions: assessing the quality of resulting images. Photogrammetric Engineering and Remote Sensing, 63: 691-699.
23. Zeng, Y., Huang, W., Liu, M., Zhang, H. And Zou, B., 2010, Fusion of satellite images in urban area: assessing the quality of resulting images. In 18th International Conference on Geoinformatics, 18-20 June 2010, Beijing, China (New York: IEEE), pp. 1-4. http://ieeexplore/ieee.org (Accessed: 1 December 2010).
24. Zhang, Y. 2002. International Archives of Photogrammetry and Remote Sensing (IAPRS), Geo Spatial Theory, Processing and Applications. Problems in the fusion of commercial high-resolution satellite images as well Landsat 7 images and initial solutions. July 20028-122002, Ottawa, ON. Silves: IAPRS.
25. Zhang, Y. 2004. Understanding image fusion. Photogrammetric Engineering and Remote Sensing, 70: 657-661.