Abstract
Building suitable image fusion techniques for remote sensing application is an emerging field of research. Though there exist quite a few algorithms in this domain, but still there is a scope of improvement in terms of quality of the fused image and reduction in the complexity of the fusion algorithms. In this paper, we have proposed a new adaptive fusion methodology, which is a modified form of the principle component analysis (PCA) technique based on a window technique. Our proposed method gives higher fusion quality compared to some of the existing standard methods, in terms of image quality and promises to be less complex. For our experiment, we have used the high spatial resolution panchromatic (PAN) image and the multispectral (MS) image, as available from remote sensing satellites such as SPOT5.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Wang, J., et al.: Review of Satellite Remote Sensing Use in Forest Health Studies. The Open Geography Journal 3, 28–42 (2010)
Li, H., Manjunath, S., Mitra, S.: Multisensor image fusion using the wavelet transform. Graphical Models and Image Processing 57(3), 235–245 (1995)
Gonzalez-Audicana, M., Saleta, J.L., Catalan, R.G., Garcia, R.: Fusion of Multispectral and Panchromatic Images Using Improved IHS and PCA Mergers Based on Wavelet Decomposition. IEEE Trans. on Geosci. and Remote Sens. 42(6), 1291–1299 (2004)
Zheng, Y., Hou, X., Bian, T., Qin, Z.: Effective Image Fusion Rules Of Multi‐scale Image Decomposition. In: Procedings of the 5th International Symposium on Image and signal Processing and Analysis, pp. 362–366 (2007)
Shi, H., Tian, B., Wang, Y.: Fusion of Multispectral and Panchromatic Satellite Images using Principal Component Analysis and Nonsubsampled Contourlet Transform. In: Processings of 10th International Conference on FSKD, pp. 2312–2315 (2010)
Tu, et al.: A fast intensity-hue-saturation fusion technique with spectral adjustment for IKONOS imagery. IEEE Geoscience and Remote Sensing Letters 1(4), 309–312 (2004)
Choi, J., Yu, K., Kim, Y.: A New Adaptive Component-Substitution-Based Satellite Image Fusion by Using Partial Replacement. IEEE Transactions on Geoscience and Remote Sensing 49(1), 295–309 (2011)
Smit, L.I.: A tutorial on Principal Component Analysis, pp. 1–27 (2002)
Li, S., Li, Z., Gong, J.: Multivariate statistical analysis of measures for assessing the quality of image fusion. International Journal of Image and Data Fusion 1(1), 47–66 (2010)
Yakhdani, M.F., Azizi, A.: Quality assessment of image fusion techniques for multisensory High resolution satellite images (case study: irs‐p5 and irs‐p6 Satellite images). In: Wagner, W., Székely, B. (eds.) ISPRS TC VII Symposium – 100 Years ISPRS, Vienna, Austria, July 5-7, vol. XXXVIII, Part 7B, pp. 204–208. IAPRS (2010)
Aiazzi, B., Baronti, S., Selva, M., Alparone, L.: MS + Pan image fusion by an enhanced Gram-Schmidt spectral sharpening. In: Bochenek, Z. (ed.) New Developments and Challenges in Remote Sensing, pp. 113–120. Mill Press, Rotterdamp (2007)
Nunez, E., Otazu, X., Fors, O., Prades, A., Palà, V., Arbiol, R.: Multiresolution-based image fusion with adaptive wavelet decomposition. IEEE Transactions on Geoscience and Remote Sensing 37(3), 1204–1211 (1999)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Sen, A.K., Mukherjee, S., Chakrabarti, A. (2014). Satellite Image Fusion Using Window Based PCA. In: Satapathy, S., Avadhani, P., Udgata, S., Lakshminarayana, S. (eds) ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol II. Advances in Intelligent Systems and Computing, vol 249. Springer, Cham. https://doi.org/10.1007/978-3-319-03095-1_32
Download citation
DOI: https://doi.org/10.1007/978-3-319-03095-1_32
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03094-4
Online ISBN: 978-3-319-03095-1
eBook Packages: EngineeringEngineering (R0)