Abstract
Image fusion is the combining process of relevant information from one or more images to create a single image with more informational content. In remote sensing applications, the spatial resolution of the multispectral images is enhanced using detail information from the panchromatic images which have a higher resolution. This process is known as pansharpening. One of the most used pansharpening method is based on wavelet decomposition. The edge information from the panchromatic image is injected in the wavelet decomposition of the multispectral image. In this paper a fusion method based on morphological wavelets is proposed. The main advantage of morphological wavelets is the computing complexity, because only integer operations are used.
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References
Aiazzi, B., Baronti, S., Selva, M.: Improving component substitution pansharpening through multivariate regression of MS+PAN data. IEEE Transactions on Geoscience and Remote Sensing 45(10), 98–102 (2007)
Alparone, L., et al.: Comparison of Pansharpening Algorithms: Outcome of the 2006 GRS-S Data-Fusion Contest. IEEE Transactions on Geoscience and Remote Sensing 45(10), 3012–3021 (2007)
Coltuc, D., Bolon, P., Chassery, J.-M.: Exact histogram specification. IEEE Transactions on Image Processing 15(5), 1143–1152 (2006)
De, I., Chanda, B.: A simple and efficient algorithm for multifocus image fusion using morphological wavelets. Signal Processing 86(5), 924–936 (2006)
Dong, J., Zhuang, D., Huang, Y., Fu, J.: Survey of Multispectral Image Fusion Techniques in Remote Sensing Applications. Image Fusion and Its Applications, Intech., 1–22 (2011)
Gomez, R.B., Jazaeri, A., Kafatos, M.: Wavelet-based hyperspectral and multispectral image fusion. In: Proc. SPIE. Geo-Spatial Image and Data Exploitation II, vol. 4383, pp. 36–42
González-Audícana, M., Saleta, J.L., Catalán, R.G., García, R.: Fusion of Multispectral and Panchromatic Images Using Improved IHS and PCA Mergers Based on Wavelet Decomposition. IEEE Transactions on Geoscience and Remote Sensing 42(6), 1291–1299 (2004)
Goutsias, J., Heijmans, H.J.: Nonlinear multiresolution signal decomposition schemes, Part 1: morphological pyramids. IEEE Trans. Image Processing 9, 1862–1876 (2000)
Heijmans, H.J., Goutsias, J.: Nonlinear multiresolution signal decomposition schemes, Part 2: morphological wavelets. IEEE Trans. Image Processing 9, 1897–1913 (2000)
Mitianoudis, N., Tzimiropoulos, G., Stathaki, T.: Fast Wavelet-based Pansharpening of Multi-Spectral Images. In: Proc. of 2010 IEEE International Conference on Imaging Systems and Techniques (IST), pp. 11–16 (2010)
Nobuhara, H., Hirota, K.: A Fuzzification of MorphologicalWavelets Based on Fuzzy Relational Calculus and its Application to Image Compression/Reconstruction. Journal of Advanced Computational Intelligence and Intelligent Informatics 8(4), 373–378 (2004)
Open Source Computer Vision Library, Reference Manual, Copyright 1999-2001 Intel Corporation
Shah, V.P., Younan, N.H., King, R.L.: An Efficient Pan-Sharpening Method via a Combined Adaptive PCA Approach and Contourlets. IEEE Transactions on Geoscience and Remote Sensing 46(5), 1323–1335 (2008)
SATELLITE IMAGING CORPORATION, http://www.satimagingcorp.com/satellite-sensors
Yang, S., Wang, M., Jiao, L.: ‘Fusion of multispectral and panchromatic images based on support value transform and adaptive principal component analysis. Information Fusion 13(3), 177–184 (2012)
Multispectral Image Database, http://www1.cs.columbia.edu/CAVE/databases/multispectral/
Global Observatory for Ecosystem Services, Michigan State University, http://landsat.org
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Bejinariu, S.I., Rotaru, F., Niţă, C.D., Costin, M. (2013). Morphological Wavelets for Panchromatic and Multispectral Image Fusion. In: Balas, V., Fodor, J., Várkonyi-Kóczy, A., Dombi, J., Jain, L. (eds) Soft Computing Applications. Advances in Intelligent Systems and Computing, vol 195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33941-7_50
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DOI: https://doi.org/10.1007/978-3-642-33941-7_50
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