Soft Computing

, Volume 21, Issue 8, pp 1977–1989

Image fusion by combining multiwavelet with nonsubsampled direction filter bank

  • Geng Peng
  • Zhengyou Wang
  • Shuaiqi Liu
  • Shanna Zhuang
Methodologies and Application

DOI: 10.1007/s00500-015-1893-0

Cite this article as:
Peng, G., Wang, Z., Liu, S. et al. Soft Comput (2017) 21: 1977. doi:10.1007/s00500-015-1893-0

Abstract

Aiming to solving the problem of too much reductancy in nonsubsampled contourlet transform and shearlet transform, a new type of transform by combining the multiwavelet transform with nonsubsampled direction filter bank is proposed. Subsequently, a multi-scale-decomposition-based image fusion approach is presented. The pulse coupled neural networks (PCNN) are motivated by the local sum-modified-Laplacian measurement of every subband coefficient. If the coefficients generate larger firing times than the other, the coefficients will be chose to synthesize the fused image. Several experiments are performed on three kinds of images, such as multi-focus images, medical images and multispectral images. The experiments indicate that the proposed fusion method observably outperforms the other multi-scale geometry analysis methods adopting the PCNN, such as the traditional wavelet, NSCT, shearlet and other latest image fusion algorithms.

Keywords

Multiwavelet NSDFB PCNN Image fusion 

Funding information

Funder NameGrant NumberFunding Note
Natural Science Fund of Hebei Province
  • F2013210094
  • F2013210109

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Geng Peng
    • 1
  • Zhengyou Wang
    • 1
  • Shuaiqi Liu
    • 2
  • Shanna Zhuang
    • 1
  1. 1.School of Information Science and TechnologyShijiazhuang Tiedao UniversityShijiazhuangPeople’s Republic of China
  2. 2.College of Electronic and Information EngineeringHebei UniversityBaodingPeople’s Republic of China

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