• Infrared Technology
  • Vol. 43, Issue 1, 13 (2021)
Sunyun YANG, Zhenghao XI, Handong WANG, Xiao LUO, and Xiu KAN
Author Affiliations
  • [in Chinese]
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    DOI: Cite this Article
    YANG Sunyun, XI Zhenghao, WANG Handong, LUO Xiao, KAN Xiu. Image Fusion Based on NSCT and Minimum-Local Mean Gradient[J]. Infrared Technology, 2021, 43(1): 13 Copy Citation Text show less
    References

    [1] MA J, MA Y, LI C. Infrared and visible image fusion methods and applications: A survey[J]. Information Fusion, 2019, 45: 153-178.

    [2] HUANG Z, CHEN L, ZHANG Y, et al. Robust contact-point detection from pantograph-catenary infrared images by employing horizontal-vertical enhancement operator[J]. Infrared Physics & Technology, 2019, 101: 146-155.

    [3] HUANG Z, FANG H, LI Q, et al. Optical remote sensing image enhancement with weak structure preservation via spatially adaptive gamma correction[J]. Infrared Physics & Technology, 2018, 94: 38-47.

    [5] ZHANG B, LU X, PEI H, et al. A fusion algorithm for infrared and visible images based on saliency analysis and non-subsampled Shearlet transform[J]. Infrared Physics & Technology, 2015, 73: 286-297.

    [6] ZHOU Z, WANG B, LI S, et al. Perceptual fusion of infrared and visible images through a hybrid multi-scale decomposition with Gaussian and bilateral filters[J]. Information Fusion, 2016, 30: 15-26.

    [7] MA J, YU W, LIANG P, et al. Fusion GAN: A generative adversarial network for infrared and visible image fusion[J]. Information Fusion, 2019, 48: 11-26.

    [8] ZHANG Y, ZHANG L, BAI X, et al. Infrared and visual image fusion through infrared feature extraction and visual information preservation[J]. Infrared Physics & Technology, 2017, 83: 227-237.

    [12] DA Cunha A L, ZHOU J, DO M N. The nonsubsampled contourlet transform: theory, design, and applications[J]. IEEE Transactions on Image Processing, 2006, 15(10): 3089-3101.

    [13] ZHU Z, YIN H, CHAI Y, et al. A novel multi-modality image fusion method based on image decomposition and sparse representation[J]. Information Sciences, 2018, 432: 516-529.

    [15] XIA Z, PENG X, FENG X, et al. Scarce face recognition via two-layer collaborative representation[J]. IET Biometrics, 2017, 7(1): 56-62.

    [20] JIN X, JIANG Q, YAO S, et al. A survey of infrared and visual image fusion methods[J]. Infrared Physics & Technology, 2017, 85: 478-501.

    [22] QU G, ZHANG D, YAN P. Information measure for performance of image fusion[J]. Electronics letters, 2002, 38(7): 313-315.

    [23] HAN Y, CAI Y, CAO Y, et al. A new image fusion performance metric based on visual information fidelity[J]. Information Fusion, 2013, 14(2): 127-135.

    CLP Journals

    [1] SUN Bin, ZHUGE Wuwei, GAO Yunxiang, WANG Zixuan. Infrared and Visible Image Fusion Based on Latent Low-Rank Representation[J]. Infrared Technology, 2022, 44(8): 853

    [2] CAO Yutong, HUAN Kewei, XUE Chao, HAN Fengdi, LI Xiangyang, CHEN Xiao. Infrared and Visible Image Fusion Based on CNN with NSCT[J]. Infrared Technology, 2023, 45(4): 378

    YANG Sunyun, XI Zhenghao, WANG Handong, LUO Xiao, KAN Xiu. Image Fusion Based on NSCT and Minimum-Local Mean Gradient[J]. Infrared Technology, 2021, 43(1): 13
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