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Fusion of Multi-spectral Image Using Non-separable Additive Wavelets for High Spatial Resolution Enhancement

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Image Analysis and Recognition (ICIAR 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6753))

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Abstract

In order to solve the problems that the image fusion method based on separable discrete wavelet transform is lower in spatial resolution and there is block effect in fused image, a new multispectral image fusion method based on non-separable wavelets with compactly support, symmetry, orthogonality, and dilation matrix [2,0;0,2] is proposed. A construction method of four channels 6 × 6 filter banks is presented. Using the low-pass filter constructed, multispectral images are fused. Three fusion methods called NAWS, NAWRGB and NAWL are proposed in the fusion of multispectral image and panchromatic image. Every fusion method presented outperforms the corresponding fusion method of the AWS, the AWRGB and the AWL in preserving high spatial resolution information respectively, and the higher spatial resolution fused image can be obtained. Of all fusion methods, the non-separable additive wavelet substitution (NAWS) method has the best performance in preserving higher spatial resolution information.

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Author information

Authors and Affiliations

  1. School of Mathematics and Computer Science, Hubei University, 430062, Wuhan, Hubei Province, China

    Bin Liu

  2. School of Computer, Wuhan University, 430079, Wuhan, Hubei Province, China

    Weijie Liu

Authors
  1. Bin Liu
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  2. Weijie Liu
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Waterloo, ON, Canada

    Mohamed Kamel

  2. Faculty of Engineering, Institute of Biomedical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

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© 2011 Springer-Verlag Berlin Heidelberg

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Liu, B., Liu, W. (2011). Fusion of Multi-spectral Image Using Non-separable Additive Wavelets for High Spatial Resolution Enhancement. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21593-3_10

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  • DOI: https://doi.org/10.1007/978-3-642-21593-3_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21592-6

  • Online ISBN: 978-3-642-21593-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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