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Image Fusion Method Based on Multi-band Wavelet Transform

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 106))

Abstract

Image fusion is one important application in information processing area. The goal of image fusion is to integrate complementary information from multi-sensor data such that the new images are more suitable for the purpose of human visual perception and computer-processing. Wavelet analysis, which has the local excellence both in time and frequency domain, has become a principal technique in image fusion. With the development of the multi-band wavelet in recent years, image fusion based on wavelet has come into a new area. We give the decomposed and reconstructed algorithm of M-band wavelet, and propose an image fusion scheme which is based on the M-band wavelet transform. By compare with the fusion scheme, we find the M-band wavelet scheme has better quality in image fusion.

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References

  1. Kokar, M.M., Tomasik, J.A., Weyman, J.: Formalizing classes of information fusion systems. Information Fusion 5, 189–202 (2004)

    Article  Google Scholar 

  2. Li, H., Manjunath, B.S., Mitra, S.K.: Multi-sensor Image Fusion Using the Wavelet Transform. Graphical Models and Image Processing 57, 235–245 (1995)

    Article  Google Scholar 

  3. Ranchin, T., Aiazzi, B., Alparone, L., Baronti, S., Wald, L.: Image fusion the ARSIS concept and some successful implementation schemes. Photogrammetry & Remote Sensing 58, 4–18 (2003)

    Article  Google Scholar 

  4. Murtagh, F., Aussem, A., Strck, J.-L.: Multi-scale Data Analysis Information Fusion and Constant-time Clustering. Multi Scale Data Analysis 41(3), 359–364 (1997)

    Google Scholar 

  5. Simone, G., Farina, A., Morabito, F.C.: Image fusion techniques for remote sensing applications. Information Fusion 3, 3–15 (2002)

    Article  Google Scholar 

  6. Yan, X.P., Zhao, C.H., Lu, Z.Y., Zhou, X.C., Xiao, H.L.: A study of information technology used in oil monitoring. Tribology International 138, 879–886 (2005)

    Article  Google Scholar 

  7. Sossai, C., Bison, P., Chemello, G., Trainito, G.: Sensor fusion for localization using possibility theory. Control Engineering Practice 7, 773–782 (1999)

    Article  Google Scholar 

  8. Pajares, G., de la Cruz, J.M.: A wavelet-based image fusion tutorial. Pattern Recognition 37, 1855–1872 (2004)

    Article  Google Scholar 

  9. Chibani, Y., Houacine, A.: Redundant versus orthogonal wavelet decomposition for multi-sensor image fusion. Pattern Recognit. 36, 879–887 (2003)

    Article  Google Scholar 

  10. Shi, W.Z., Zhu, C.Q., Zhu, S.L.: Fusing IKONOS images based on four-band wavelet transformation method. Information Fusion Submitted for Publication (2005)

    Google Scholar 

  11. Shi, W., Zhu, C., Tian, Y., Nichol, J.: Wavelet-based image fusion and quality assessment. Applied Earth Observation and Geo-information 6, 241–251 (2005)

    Article  Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Wang, Y. (2011). Image Fusion Method Based on Multi-band Wavelet Transform. In: Jin, D., Lin, S. (eds) Advances in Computer Science, Intelligent System and Environment. Advances in Intelligent and Soft Computing, vol 106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23753-9_25

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  • DOI: https://doi.org/10.1007/978-3-642-23753-9_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23752-2

  • Online ISBN: 978-3-642-23753-9

  • eBook Packages: EngineeringEngineering (R0)

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