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  • 标题:Feature-Based Image Fusion with a Uniform Discrete Curvelet Transform
  • 本地全文:下载
  • 作者:Liang Xu ; Junping Du ; Qian Hu
  • 期刊名称:International Journal of Advanced Robotic Systems
  • 印刷版ISSN:1729-8806
  • 电子版ISSN:1729-8814
  • 出版年度:2013
  • 卷号:10
  • DOI:10.5772/56345
  • 语种:English
  • 出版社:SAGE Publications
  • 摘要:The uniform discrete curvelet transform (UDCT) is a novel tool for multiscale representations with several desirable properties compared to previous representation methods. A novel algorithm based on UDCT is proposed for the fusion of multi-source images. A novel fusion rule for different subband coefficients obtained by UDCT decomposition is discussed in detail. Low-pass subband coefficients are merged to develop a fusion rule based on a feature similarity (FSIM) index. High-pass directional subband coefficients are merged for a fusion rule based on a complex coefficients feature similarity (CCFSIM) index. Experimental results demonstrate that the proposed algorithm fuses all of the useful information from source images without introducing artefacts. Compared with several state-of-the-art fusion methods, it yields a better performance and achieves higher efficiency.
  • 关键词:Image Fusion; UDCT; FSIM Index; CCFSIM Index
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