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Infrared and Visible Image Fusion Based on Morphological Image Enhancement of Dual-Tree Complex Wavelet

  • Changxing LiEmail author
  • Liu LeiEmail author
  • Xiaolu ZhangEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1075)

Abstract

To compensate for the problems that arise during infrared and visible image fusion, such as lack of detailed information, ringing, incomplete scene information, low contrast, and “virtual shadow”. Based on the orthogonal discrete Q-shift dual-tree filter, an image fusion method combined with morphological image enhancement and dual-tree complex wavelet is proposed. Firstly, the morphological opening and closing operations are used to enhance the source image. Secondly, the enhanced image is decomposed into high-low frequency subbands by the dual-tree complex wavelet filter, and the low frequency subbands adopt a local mean fusion method according to the degree of correlation. The high frequency subbands image adopt the fusion principle of absolute maximum; finally, fusion image obtained by reconstruction. Comparing the experimental results, the proposed method significantly improves the image fusion quality indexes such as average gradient, information entropy, spatial frequency and standard deviation.

Keywords

Image fusion Morphological image enhancement Double-tree complex wavelet transform Region correlation Absolute maximum 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.School of ScienceXi’an University of Posts and TelecommunicationsXi’anChina
  2. 2.School of Communication and InformationXi’an University of Posts and TelecommunicationsXi’anChina

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