• Opto-Electronic Engineering
  • Vol. 46, Issue 1, 180084 (2019)
Qi Yubin1, Yu Mei1、2、*, Jiang Hao1、3, Shao Hua1, and Jiang Gangyi1、2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • show less
    DOI: 10.12086/oee.2019.180084 Cite this Article
    Qi Yubin, Yu Mei, Jiang Hao, Shao Hua, Jiang Gangyi. Multi-exposure image fusion based on tensor decomposition and convolution sparse representation[J]. Opto-Electronic Engineering, 2019, 46(1): 180084 Copy Citation Text show less
    References

    [1] Artusi A, Richter T, Ebrahimi T, et al. High dynamic range imaging technology[J]. IEEE Signal Processing Magazine, 2017, 34(5): 165–172.

    [2] Chiang J C, Kao P H, Chen Y S, et al. High-dynamic-range image generation and coding for multi-exposure multi-view images[J]. Circuits, Systems, and Signal Processing, 2017, 36(7): 2786–2814.

    [3] Du L, Sun H Y, Wang S, et al. High dynamic range image fusion algorithm for moving targets[J]. Acta Optica Sinica, 2017, 37(4): 101–109.

    [4] Li S T, Kang X D, Fang L Y, et al. Pixel-level image fusion: a survey of the state of the art[J]. Information Fusion, 2017, 33: 100–112.

    [5] Zhao C H, Guo Y T, Wang Y L. A fast fusion scheme for infrared and visible light images in NSCT domain[J]. Infrared Physics & Technology, 2015, 72: 266–275.

    [6] Chen C, Li Y Q, Liu W, et al. Image fusion with local spectral consistency and dynamic gradient sparsity[C]//Proceedings of 2014 IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, USA, 2014: 2760–2765.

    [7] Sun J, Zhu H Y, Xu Z B, et al. Poisson image fusion based on Markov random field fusion model[J]. Information Fusion, 2013, 14(3): 241–254.

    [8] Liu Y, Liu S P, Wang Z F. A general framework for image fusion based on multi-scale transform and sparse representation[J]. Information Fusion, 2015, 24: 147–164.

    [9] Mertens T, Kautz J, van Reeth F. Exposure fusion: a simple and practical alternative to high dynamic range photography[J]. Computer Graphics Forum, 2009, 28(1): 161–171.

    [10] Li S T, Kang X D, Hu J W. Image fusion with guided filtering[J]. IEEE Transactions on Image Processing, 2013, 22(7): 2864–2875.

    [11] Liu Y, Wang Z F. Dense SIFT for ghost-free multi-exposure fusion[J]. Journal of Visual Communication and Image Representation, 2015, 31: 208–224.

    [12] Ma K D, Li H, Yong H W, et al. Robust multi-exposure image fusion: a structural patch decomposition approach[J]. IEEE Transactions on Image Processing, 2017, 26(5): 2519–2532.

    [13] Ma K D, Duanmu Z F, Yeganeh H, et al. Multi-exposure image fusion by optimizing a structural similarity index[J]. IEEE Transactions on Computational Imaging, 2018, 4(1): 60–72.

    [14] Kolda T G, Bader B W. Tensor decompositions and applications[J]. SIAM Review, 2009, 51(3): 455–500.

    [15] Wang H Z, Ahuja N. A tensor approximation approach to dimensionality reduction[J]. International Journal of Computer Vision, 2008, 76(3): 217–229.

    [16] Zeiler M D, Krishnan D, Taylor G W, et al. Deconvolutional networks[C]//Proceedings of 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, 2010: 2528–2535.

    [17] Chen S S, Donoho D L, Saunders M A. Atomic decomposition by basis pursuit[J]. SIAM Journal on Scientific Computing, 1998, 20(1): 33–61.

    [18] Wohlberg B. Efficient algorithms for convolutional sparse representations[J]. IEEE Transactions on Image Processing, 2016, 25(1): 301–315.

    [19] Liu J L, Garcia-Cardona C, Wohlberg B, et al. Online convolutional dictionary learning[C]//Proceedings of 2017 IEEE International Conference on Image Processing, Beijing, China, 2017.

    [20] Liu Y, Chen X, Ward R K, et al. Image fusion with convolutional sparse representation[J]. IEEE Signal Processing Letters, 2016, 23(12): 1882–1886.

    [21] Paul S, Sevcenco I S, Agathoklis P. Multi-exposure and multi-focus image fusion in gradient domain[J]. Journal of Circuits, Systems, and Computers, 2016, 25(10): 1650123.

    [22] Banterle F, Artusi A, Debattista K, et al. Advanced High Dynamic Range Imaging: Theory and Practice[M]. Natick, MA: A K Peters, 2011.

    [23] Ma K D. Multi-Exposure Image Fusion by Optimizing A Structural Similarity Index[DB/OL]. https://ece.uwaterloo.ca/ ~k29ma/dataset/MEFOpt_Database, 2018.

    [24] Xydeas C S, Petrovic V. Objective image fusion performance measure[J]. Electronics Letters, 2000, 36(4): 308–309.

    Qi Yubin, Yu Mei, Jiang Hao, Shao Hua, Jiang Gangyi. Multi-exposure image fusion based on tensor decomposition and convolution sparse representation[J]. Opto-Electronic Engineering, 2019, 46(1): 180084
    Download Citation