[1] A. A. Goshtasby and S. Nikolov, Image fusion: Advances in the
state of the art, Inf. Fusion 8(2) (2007), 114-118.
[2] Y. Liu and Z. Wang, Simultaneous image fusion and denoising with
adaptive sparse representation, IET Image Processing, 2014.
Online, DOI: 10.1049/iet-ipr.2014.0311
[3] W. Huang and Z. Jing, Evaluation of focus measures in multi-focus
image fusion, Pattern Recognition Letters 28(4) (2007), 493-500.
[4] Y. H. Jia, Fusion of Landsat TM and SAR images based on principal
component analysis, Remote Sensing Technology and Application 13(1)
(1998), 46-49.
[5] T. Wan, C. C. Zhu and Z. C. Qin, Multifocus image fusion based on
robust principal component analysis, Pattern Recognition Letters 34(9)
(2013), 1001-1008.
[6] S. T. Li, X. D. Kang and J. W. Hu, Image fusion with guided
filtering, IEEE Transactions on Image Processing 22(7) (2013),
2864-2875.
[7] G. Pajares and J. M. Cruz, A wavelet-based image fusion tutorial,
Pattern Recognition 37(9) (2004), 1855-1872.
[8] Y. Chai, H. Li and Z. Li, Multifocus image fusion scheme using
focused region detection and multiresolution, Optics Communications
284(19) (2011), 4376-4389.
[9] P. Geng, M. Huang and S. Q. Liu et al., Multifocus image fusion
method of ripplet transform based on cycle spinning, Multimedia Tools
and Applications (2014), 1-11.
[10] S. Q. Liu, J. Zhao and P. Geng et al., Medical image fusion based
on nonsubsampled direction complex wavelet transform, International
Journal of Applied Mathematics and Machine Learning 1(1) (2014),
21-34.
[11] X. B. Qu, J. W. Yan and G. D. Yang, Sum-modified-Laplacian-based
multi-focus image fusion method in sharp frequency localized
contourlet transform domain, Optics and Processing Engineering 17(5)
(2009), 1203-1212.
[12] X. B. Qu, J. W. Yan and H. Z. Xiao et al., Image fusion algorithm
based on spatial frequency-motivated pulse coupled neural networks in
nonsubsampled contourlet transform domain, Acta Automatica Sinica
34(12) (2008), 1508-1514.
[13] Q. G. Miao, C. Shi and P. F. Xu, A novel algorithm of image
fusion using shearlets, Optics Communications 284(6) (2011),
1540-1547.
[14] P. Geng, Z. Wang and Z. Zhang et al., Image fusion by pulse
couple neural network with shearlet, Optical Engineering 51(6) (2012),
067005-1-067005-7.
[15] Q. Zhang, L. Wang and Z. Ma et al., A novel video fusion
framework using surfacelet transform, Optics Communications 285(13)
(2012), 3032-3041.
[16] L. Chen, J. Li and C. L. Chen, Regional multifocus image fusion
using sparse representation, Optics Express 21(4) (2013),
5182-5197.
[17] S. B. Gao, Y. M. Cheng and Y. Q. Zhao, Method of visual and
infrared fusion for moving object detection, Optics Letters 38(11)
(2013), 1981-1983.
[18] D. Guo, J. Yan and X. Qu, High quality multi-focus image fusion
using self-similarity and depth information, Optics Communications
338(1) (2015), 138-144.
[19] S. Q. Liu, S. H. Hu and Y. Xiao, SAR image de-noised based on
wavelet-contourlet transform with cycle spinning, Signal Processing
27(6) (2011), 837-842. (Chinese)
[20] G. Easley, D. Labate and W. Q. Lim, Sparse directional image
representation using the discrete shearlets transform, Applied and
Computational Harmonic Analysis 25(1) (2008), 25-46.
[21] G. Kutyniok, J. Lemvig and W. Q. Lim, Compactly supported
shearlets are optimally sparse, Journal of Approximation Theory
163(11) (2011), 1564-1589.
[22] W. Q. Lim, The discrete shearlets transform: A new directional
transform and compactly supported shearlets frames, IEEE Trans. Image
Proc. 19(5) (2010), 1166-1180.
[23] S. Liu, S. Hu and Y. Xiao, Image separation using wavelet-complex
shearlet dictionary, Journal of Systems Engineering and Electronics
25(2) (2014), 314-321.
[24] W. Kong, L. Zhang and Y. Lei, Novel fusion method for visible
light and infrared images based on NSST–SF–PCNN, Infrared Physics
& Technology 65 (2014), 103-112.
[25] S. Q. Liu, S. H. Hu and Y. Xiao et al., Bayesian shearlet
shrinkage for SAR image de-noising via sparse representation,
Multidimensional Systems and Signal Processing 25(4) (2014),
683-701.
[26] X. B. Qu, Y. Hou and F. Lam et al., Magnetic resonance image
reconstruction from undersampled measurements using a patch-based
nonlocal operator, Medical Image Analysis 18(6) (2014), 843-856.
[27] S. Zhuo and T. Sim, Defocus map estimation from a single image,
Pattern Recognition 44(9) (2011), 1852-1858.