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Remote Sensing Image Fusion Based on Shearlet and Genetic Algorithm

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Bio-Inspired Computing -- Theories and Applications (BIC-TA 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 562))

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Abstract

Image fusion is a technology which can effectively enhance the utilization ratio of image information, the accuracy of target recognition and the interpretation ability of image. However, traditional fusion methods may lead to the information loss and image distortion. Hence a novel remote sensing image fusion method is proposed in this paper. As one of the multi-scale geometric analysis tools, Shearlet has been widely used in image processing. In this paper, Shearlet is used to decompose the image. Genetic Algorithm, a intelligent optimization algorithm, is also applied to image fusion and it aims to optimize the weighted factors in order to improve the quality of fusion. Experimental results prove the superiority and feasibility of this method.

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Author information

Authors and Affiliations

  1. School of Computer and Technology, Xidian University, Xi’an, China

    Qiguang Miao, Ruyi Liu, Yiding Wang, Jianfeng Song, Yining Quan & Yunan Li

Authors
  1. Qiguang Miao
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  2. Ruyi Liu
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  3. Yiding Wang
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  4. Jianfeng Song
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  5. Yining Quan
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  6. Yunan Li
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Corresponding author

Correspondence to Qiguang Miao .

Editor information

Editors and Affiliations

  1. Xidian University, Xi'an, China

    Maoguo Gong

  2. Huazhong Univ. of Science and Technology, Wuhan, China

    Pan Linqiang

  3. University of Petroleum, Qingdao, China

    Song Tao

  4. University of Science and Technology of China, Hefei, China

    Ke Tang

  5. Anhui University, Hefei, China

    Xingyi Zhang

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© 2015 Springer-Verlag Berlin Heidelberg

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Miao, Q., Liu, R., Wang, Y., Song, J., Quan, Y., Li, Y. (2015). Remote Sensing Image Fusion Based on Shearlet and Genetic Algorithm. In: Gong, M., Linqiang, P., Tao, S., Tang, K., Zhang, X. (eds) Bio-Inspired Computing -- Theories and Applications. BIC-TA 2015. Communications in Computer and Information Science, vol 562. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49014-3_26

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  • DOI: https://doi.org/10.1007/978-3-662-49014-3_26

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49013-6

  • Online ISBN: 978-3-662-49014-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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