DOI QR코드

DOI QR Code

Fitting to Panchromatic Image for Pansharpening Combining Point-Jacobian MAP Estimation

  • Published : 2008.10.31

Abstract

This study presents a pansharpening method, so called FitPAN, to synthesize multispectral images at a higher resolution by exploiting a high-resolution image acquired in panchromatic modality. FitPAN is a modified version of the quadratic programming approach proposed in (Lee, 2008), which is designed to generate synthesized multispectral images similar to the multispectral images that would have been observed by the corresponding sensor at the same high resolution. The proposed scheme aims at reconstructing the multispectral images at the higher resolution with as less spectral distortion as possible. This study also proposes a sharpening process to eliminate some distortions appeared in the fused image of the higher resolution. It employs the Point-Jacobian MAP iteration utilizing the contextual information of the original panchromatic image. In this study, the new method was applied to the IKONOS 1m panchromatic and 4m multispectral data, and the results were compared with them of several current approaches. Experimental results demonstrate that the proposed scheme can achieve significant improvement in both spectral and block distortion.

Keywords

References

  1. Aiazzi, B., L. Alparone, S. Baronti, and A. Garzelli, 2002. Context-driven fusion of high spatial and spectral resolution images based on oversampled multiresolution analysis, IEEE Trans. Geosci. Remote Sens., 40: 2300-2312 https://doi.org/10.1109/TGRS.2002.803623
  2. Alparone, L., L. Wald, J. Chanussot, C. Thomas, P. Gamba, and L. M. Bruce, 2006. Comparison of pansharpening algoriths: Outcome of the 2006 GRS-S data-fusion contest, IEEE Trans. Geosci. Remote Sensing, 45: 3012-3021 https://doi.org/10.1109/TGRS.2007.904923
  3. Carper , W., T. Lillesand, and R. Kiefer, 1990. The use of intensity-hue-saturation transformations for merging Spot panchromatic and multispectral image data, Photogram. Eng. Remote Sensing, 56: 459-467
  4. Chavez, P. S., S. C. Sildes, and J. A. Anderson, 1991. Comparison of three different methods to merge multiresolution and multispectral data: Landsat TM and SPOT panchromatic, Photogramm. Eng. Rem. Sens., 57: 295-303
  5. Civco, D. L., Y. Wang, and J. A. Silander, 1995. Characterizing forest ecosystems in Connecticut by integrating Landsat TM and SPOT panchromatic data, Proc.1995 Annual ASPRS/ACSM Convention, Charlotte, NC., 2: 216-224
  6. Gill, P. E., W. Murray, and M. H. Wright, 1991. Numerical Linear Algebra and Optimization, Vol. 1, Addison Wesley
  7. Laben, C. A.and B. V. Brower, 2000. Process for enhancing the spatial resoltion of multispectral imagery using pan-sharpening, Technical Report US Patent #6,110,875, Eastman Kodak Company
  8. Lee, S-H, 2007. Adaptive Iterative Despeckling of SAR Imagery, Korean J. Remote sens., 23: 455-464 https://doi.org/10.7780/kjrs.2007.23.5.455
  9. Lee, S-H, 2008. Quadratic Programming Approach to Pansharpening of Multispectral Images Using a Regression Model, Korean J. Remote sens., 24: 257-267 https://doi.org/10.7780/kjrs.2008.24.3.257
  10. Lee S. and M. M. Crawford, 1991. An Adaptive Reconstruction System for Spatially Correlated Multispectral Multitemporal Images, IEEE Trans. Geosci. Remote Sens., 29: 494-508 https://doi.org/10.1109/36.135811
  11. Mallet, S. G., 1989. A theory for multiresolution signal decomposition: the wavelet representation, IEEE Trans.Pattern Anal. Mach. Intel., 11: 674-693 https://doi.org/10.1109/34.192463
  12. Nunez, J., X. Otazu, O. Fors, A. Prades, V. Pala, and R. Arbiol, 1999. Multiresolution-based image fusion with additive wavelet decomposition, IEEE Trans. Geosci. Remote Sens., 37: 1204-1211 https://doi.org/10.1109/36.763274
  13. Otazu, X., M. Gonzales Audicana, O. Fors, and J. Nunez, 2005. Introduction of sensor spectral response into image fusion methods: Application to wavelet-based methods, IEEE Trans. Geosci. Remote Sens., 43: 2376-2385 https://doi.org/10.1109/TGRS.2005.856106
  14. Wald, L., T. Ranchin, and M. Mangolini, 1997. Fusion of satellite images of different spatial resolutions: Assessing the quality of resulting images, Photogramm. Eng. Remote Sens., 63: 691-699
  15. Yocky, D. A., 1996. Multiresolution wavelet decomposition image merger of landsat thematic mapper and spot panchromatic data, Photogramm. Eng. Rem. Sens., 69: 1067-1074
  16. Zhang, Y and G. Hong, 2005. An IHS and wavelet integrated approach to improve pansharpening visual quality of natural colur IKONS and QuickBird images, Information Fusion, 6: 225-234 https://doi.org/10.1016/j.inffus.2004.06.009