Vol. 24

Front:[PDF file] Back:[PDF file]
Latest Volume
All Volumes
All Issues

Quality Assessment of Fused Image of Modis and Palsar

By Kumar Harish and Dharmendra Singh
Progress In Electromagnetics Research B, Vol. 24, 191-221, 2010


It is a current need of research to extensively use the freely available satellite images. The most commonly available satellite images are Moderate Resolution Imaging Spectroradiometer (MODIS) and The Advanced Very High Resolution Radiometer (AVHRR). The problems with these images are their poor spatial resolution that restricts their use in various applications. This restriction may be minimized by application of the fusion techniques where high resolution image will be used to fuse with low resolution images. Another important aspect of fusion of different sensors data as optical and radar images (where both can provide the complimentary information), and the resultant fused image after fusion may give enhanced and useful information that may be beneficial for various application. Therefore, in this paper an attempt has been made to fuse the full polarimetric Phased Arraytype L-band SAR(PALSAR) image with MODIS image and assess the quality of fused image. PALSAR image has a advantage of availability of data in four different channels. These four channels are HH (Transmitted horizontal polarization and received also in horizontal polarization), HV (Transmitted horizontal polarization and received vertical polarization), VH (Transmitted vertical polarization and received horizontal polarization) and VV (Transmitted vertical polarization and received vertical polarization), which provides various landcover information. The curvelet based fusion technique has been applied to MODIS band 1 and 2 and PALSAR HH (HV and VV bands for assessing the effect of fusion in land cover distinction). The three major land covers agriculture, urban and water are considered for evaluation of fusion of these images for the Roorkee area of India. The results are quite encouraging, and in near future it may provide a better platform for maximize the use of MODIS images.


Kumar Harish and Dharmendra Singh, "Quality Assessment of Fused Image of Modis and Palsar," Progress In Electromagnetics Research B, Vol. 24, 191-221, 2010.


    1. Pohl, C. and J. L. van Genderen, "Multisensor image fusion in remote sensing: Concepts, methods, and applications," International Journal of Remote Sensing, Vol. 19, No. 5, 823-854, 1998.

    2. Shen, S. S., "Summary of types of data fusion methods utilized in workshop papers," Proceedings of Multisource Data Integration in Remote Sensing Workshop NASA Conference Publication 3099, 145-149, Greenbelt, Maryland, June 14-15, 1990.

    3. Brisco, B. and R. J. Brown, "Multidate SAR/TM synergism for crop classification in western Canada," Photogrammetric Engineering and Remote Sensing, Vol. 61, No. 7, 1009-1014, 1995.

    4. Harris, J. R., R. Murray, and T. Hirose, "IHS transform for the integration of radar imagery and other remotely sensed data," Photogrammetric Engineering and Remote Sensing, Vol. 56, No. 11, 1631-1641, 1990.

    5. Raghavawamy, V., N. C. Gautam, M. Padmavathi, and K. V. S. Badarinath, "Studies on microwave remote sensing data in conjunction with optical data for land use/land cover mapping and assessment," Geocarto International, Vol. 11, No. 4, 25-31, 1996.

    6. Welch, R. and M. Ehlers, "Cartographic feature extraction with integrated SIR-B and Landsat TM images," International Journal of Remote Sensing, Vol. 9, No. 5, 873-889, 1988.

    7. Richards, J. A. and X. Jia, Remote Sensing Digital Image Analysis --- An Introduction, 4 Ed., Springer, 2005.

    8. Alparone, L., S. Baronti, A. Garzelli, and F. Nencini, "Landsat ETM+ and SAR image fusion based on generalized intensity modulation," IEEE Transactions on Geoscience and Remote Sensing, Vol. 42, No. 11, 2832-2839, 2004.

    9. Amarsaikhan, D. and T. Douglas, "Data fusion and multisource image classification," International Journal of Remote Sensing, Vol. 25, No. 14, 3529-3539, 2004.

    10. Hegarat-Mascle, S. L., A. Quesney, D. Vidal-Madjar, O. Taconet, M. Normand, and C. Loumagne, "Land cover discrimination from multitemporal ERS images and multispectral Landsat images: A study case in an agricultural area in France," International Journal of Remote Sensing, Vol. 21, 435-456, 2000.

    11. Edwards, K. and P. A. Davis, "The use of Intensity-Hue-Saturation transformation for producing color shaded-relief images," Photogramm. Eng. Remote Sens., Vol. 60, No. 11, 1369-1374, 1994.

    12. Schetselaar, E. M., "Fusion by the IHS transform: Should we use cylindrical or spherical coordinates?," Int. J. Remote Sens., Vol. 19, No. 4, 759-765, 1998.

    13. Gillespie, A. R., A. B. Kahle, and R. E. Walker, "Color enhancement of highly correlated images --- II. Channel ratio and `chromaticity' transformation techniques," Remote Sens. Environ., Vol. 22, 343-365, 1987.

    14. Zhou, J., 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, 734-757, 1998.

    15. Chavez, P. S. and A. Y. Kwarteng, "Extracting spectral contrast in Landsat Thematic Mapper image data using selective principle component analysis," Photogramm. Eng. Remote Sens., Vol. 55, No. 3, 339-348, 1989.

    16. Pajares, G. and J. M. de la Cruz, A Wavelet-based Image Fusion Tutorial, Pattern Recognition 37, 1855-1872, Elsevier Ltd, 2004.

    17. Yocky, D. A., "Artifacts in wavelet image merging," Optical Engineering, Vol. 35, No. 6, 2094-2101, 1996.

    18. Gonzáles Audícana, M., J. L. Saleta, R. García Catalán, and R. García, "Fusion of multispectral and panchromatic images using improved IHS and PCA mergers based on wavelet decomposition," IEEE Transactions on Geoscience and Remote Sensing, Vol. 42, No. 6, 1291-1299, 2004.

    19. Starck, J. L., E. J. Candès, and D. L. Donoho, "The curvelet transform for image denoising," IEEE Trans. Image Processing, Vol. 11, 670-684, 2002.

    20. Do, M. N. and M. Vetterli, "The finite ridgelet transform for image representation," IEEE Transactions on Image Processing, Vol. 12, No. 1, 16-28, 2003.

    21. Justice, C. O., et al., "The Moderate Resolution Imaging Spectroradiometer (MODIS): Land remote sensing for global change research," IEEE Transactions on Geoscience and Remote Sensing, Vol. 36, 1228-1249, 1998.

    22. Rosenqvist, A., M. Shimada, N. Ito, and M. Watanabe, "ALOS PALSAR: A pathfinder mission for global-scale monitoring of the environment," IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, 3307-3316, 2007.

    23. Shensa, M. J., "The discrete wavelet transform: Wedding the à trous and Mallat algoritm," IEEE Trans. Signal Process., Vol. 40, No. 9, 2462-2482, 1992.

    24. Filippo, N., A. Garzelli, S. Baronti, and L. Alparone, "Remote sensing image fusion using the curvelet transform," Information Fusion, Vol. 8, 143-156, 2007.

    25. Choi, M., R. Y. Kim, and M. G. Kim, "The curvelet transform for image fusion," International Society for Photogrammetry and Remote Sensing, ISPRS 2004, Vol. 35, Part B8, 59-64, Istanbul, 2004.

    26. Choi, M., R. Y. Kim, M. R. Nam, and H. O. Kim, "Fusion of multispectral and panchromatic satellite images using the curveletv transform," IEEE Geosci. Remote Sensing Lett., Vol. 2, No. 2, 136-14, 2005.

    27. Wald, L., T. Ranchin, and M. Mangolini, "Fusion of satellite images of di®erent spatial resolutions: Assessing the quality of resulting images," Photogramm. Eng. Remote Sens., Vol. 63, No. 5, 691-699, 1997.

    28. Acerbi-Junior, F. W., J. G. P. W. Clevers, and M. E. Schaepman, "The assessment of multi-sensor image fusion using wavelet transforms for mapping the Brazilian Savanna," International Journal of Applied Earth Observation and Geoinformation, Vol. 8, 278-288, 2006.

    29. Vijayaraj, V., N. H. Younan, and C. G. O'Hara, "Quality metrics for multispectral image processing," Proceedings of the Annual ASPRS Conference, 2004.

    30. Karathanassi comparison study on fusion methods using evaluation indicators, V., P. Kolokousis, and S. Ioannidou, "A ," International Journal of Remote Sensing, Vol. 28, No. 9, 2309-2341, 2007.

    31. Li, S., J. T. Kwok, and Y. Wang, "Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images," Information Fusion, Vol. 3, 17-23, 2002.

    32. De Bethune, S., F. Muller, and J.-P. Donnay, "Fusion of multispectral and panchromatic images by local mean and variance matching filtering techniques," Proceedings of Fusion of Earth Data, 31-37, National Remote Sensing Agency, Hyerabad, 1998.

    33. Li, Q. and Q. Hu, "3D wavelet compression to multiple band remote sensing images based on edge reservation," Proceedings of the ISPRS, Commission VII, No. 11, Istanbul, 2004.

    34. Wang, Z. and A. C. Bovic, "A universal image quality index," IEEE Signal Processing Letters, Vol. 9, 81-84, 2002.

    35. SARSCAPE help document (provided by SARSCAPE),.