Abstract
On the basis of analyzing the performances of popular image fusion methods, a new remote sensing image fusion method based on principal component analysis (PCA), high pass filter (HPF) and undecimated discrete wavelet transform (UDWT) is proposed. Some measure parameters are suggested to evaluate the fusion method. Experiments have been performed with the SPOT panchromatic image and the TM multi-spectral image. Both subjectively qualitative analysis and objectively quantitative evaluation verify the performance of the new method. With the same wavelet transform level, the fusion image using the proposed method preserves more sophisticated spatial details and distorts less spectral information in comparison with the fusion image using the traditional discrete wavelet transform (DWT) method.
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© 2006 Springer-Verlag Berlin Heidelberg
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Liu, W., Huang, J., Zhao, Y. (2006). Image Fusion Based on PCA and Undecimated Discrete Wavelet Transform. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893257_54
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DOI: https://doi.org/10.1007/11893257_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46481-5
Online ISBN: 978-3-540-46482-2
eBook Packages: Computer ScienceComputer Science (R0)