Instrumentation & Measurement Magazine 24-2 - 52

[11]	S. Singh and R.S. Anand, " Multimodal medical image fusion

fusion model using sparse K-SVD dictionary learning in

mapping and structural clustering, " IEEE Trans. Instrum. Meas.,

nonsubsampled shearlet domain, " IEEE Trans. Instrum. Meas., vol.
69, no. 2, pp. 593-607, 2020.

vol. 69, no. 2, pp. 3855-3865, 2020.
[12]	X. Jin, Q. Jiang, X. Chu, X. Lang, S. Yao, K. Li, and W. Zhou, " Brain
medical image fusion using L2-norm-based features and fuzzyweighted measurements in 2-D littlewood-paley EWT domain, "
IEEE Trans. Instrum. Meas., vol. 69, no. 8, pp. 5900-5913, 2020.
[13]	S. Li, X. Kang, L. Fang, J. Hu, and H. Yin, " Pixel-level image
fusion: a survey of the state of the art, " Information Fusion, vol. 33,

[30]	H. Yin, S. Li, and L. Fang, " Simultaneous image fusion and superresolution using sparse representation, " Information Fusion, vol.
14, pp. 229-240, 2013.
[31]	H. Li, X. He, D. Tao, Y. Tang, and R. Wang, " Joint medical image
fusion, denoising and enhancement via discriminative low-rank
sparse dictionaries learning, " Pattern Recognition, vol. 79, pp.
130-146, 2018.

pp. 100-112, 2017.
[14]	J. Du, W. Li, K. Lu, and B. Xiao, " An overview of multi-modal
medical image fusion, " Neurocomputing, vol. 215, pp. 3-20, 2016.
[15]	Q. Zhang, Y. Liu, R. Blum, J. Han, and D. Tao, " Sparse
representation based multi-sensor image fusion for multi-focus
and multi-modality images: a review, " Information Fusion, vol. 40,

[32]	D. Baron, M.B. Wakin, M.F. Duarte, S. Sarvotham, and R.G.
Baraniuk, " Distributed compressed sensing, " IEEE Trans. Inf.
Theory, vol. 52, no. 12, pp. 5406-5425, 2006.
[33]	J. Starck, M. Elad, and D. Donoho, " Redundant multiscale
transforms and their application for morphological component
separation, " Adv. Imag. Electron Phys., vol. 132, pp. 287-348, 2004.

pp. 57-75, 2018.
[16]	B. Yang and S. Li, " Multi-focus image fusion and restoration with
sparse representation, " IEEE Trans. Instrum. Meas., vol. 59, no. 4,

[34]	N. Yu, T. Qiu, F. Bi, and A. Wang, " Image features extraction and
fusion based on joint sparse representation, " IEEE J. Sel. Topics
Signal Process., vol. 5, no. 5, pp. 1074-1082, 2011.

pp. 884-892, 2010.
[17]	B. Olshausen and J. Field, " Emergence of simple-cell receptive
field properties by learning a sparse code for natural images, "
Nature, vol. 381, no. 6583, pp. 607-609, 1996.
[18]	S. Mallat and Z. Zhang, " Matching pursuits with time-frequency
dictionaries, " IEEE Trans. Signal Process., vol. 41, no. 12, pp. 3397-

[35]	H. Yin and S. Li, " Multimodal image fusion with joint sparsity
model, " Opt. Eng., vol. 50, no. 6, pp. 1-10, 2011.
[36]	Q. Zhang, Y. Fu, H. Li, and J. Zou, " Dictionary learning method
for joint sparse representation-based image fusion, " Opt. Eng.,
vol. 52, no. 5, pp. 1-11, 2013.
[37]	Y. Jiang and M. Wang, " Image fusion with morphological

3415, 1993.
[19]	B. Yang and S. Li, " Pixel-level image fusion with simultaneous
orthogonal matching pursuit, " Information Fusion, vol. 13, no. 1,

component analysis, " Information Fusion, vol. 18, no. 1, pp. 107118, 2014.
[38]	J. Bobin, J. L. Starck, J. M. Fadili, Y. Moudden, and D. L. Donoho.

pp, 10-19, 2012.
[20]	M. Aharon, M. Elad, and A. Bruckstein, " K-SVD: an algorithm for
designing overcomplete dictionaries for sparse representation, "
IEEE Trans. Signal Process., vol. 54, no. 11, pp. 4311-4322, 2006.
[21]	S. Li, H. Yin, and L. Fang, " Group-sparse representation with
dictionary learning for medical image denoising and fusion, "
IEEE Trans. Biomed. Eng., vol. 59, no. 12, pp. 3450-3459, 2012.
[22]	Y. Liu and Z. Wang, " Simultaneous image fusion and denosing
with adaptive sparse representation, " IET Image Process., vol. 9,

" Morphological component analysis: An adaptive thresholding
strategy, " IEEE Trans. Image Process., vol. 16, no. 11, pp. 2675-2681,
2007.
[39]	B. Wohlberg, " Efficient algorithms for convolutional sparse
representation, " IEEE Trans. Image Process., vol. 25, no. 1, pp. 301315, 2016.
[40]	H. Bristow, A. Eriksson, and S. Lucey, " Fast convolutional sparse
coding, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., pp. 391398, 2013.

no. 5, pp. 347-357, 2015.
[23]	J. Zong and T. Qiu, " Medical image fusion based on sparse
representation of classified image patches, " Biomedical Signal
Processing and Control, vol. 34, pp. 195-205, 2017.
[24]	J. Mairal, F. Bach, J. Ponce, and G. Sapiro, " Online learning for

[41]	F. Heide, W. Heidrich, and G. Wetzstein, " Fast and flexible
convolutional sparse coding, " in Proc. IEEE Conf. Comput. Vis.
Pattern Recognit., pp. 5135-5143, 2015.
[42]	S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein,

matrix factorization and sparse coding, " J. Mach. Learn. Res., vol.

" Distributed optimization and statistical learning via the

11, pp. 19-60, 2010.

alternating direction method of multipliers, " Found. Trends Mach.

[25]	M. Kim, D. K. Han, and H. Ko, " Joint patch clustering-based
dictionary learning for multimodal image fusion, " Information

Learn., vol. 3, no. 1, pp. 1-122, 2010.
[43]	Y. Liu, X. Chen, R. Ward, and Z. Wang, " Image fusion with
convolutional sparse representation, " IEEE Signal Process. Lett.,

Fusion, vol. 27, pp. 198-214, 2016.
[26]	Z. Zhu, Y. Chai. H. Yin, Y. Li, and Z. Liu, " A novel dictionary
learning approach for multi-modality medical image fusion, "
Neurocomputing, vol. 214, pp. 471-482, 2016.
[27]	Y. Liu, S. Liu, and Z. Wang, " A general framework for image
fusion based on multi-scale transform and sparse representation, "
Information Fusion, vol. 24, pp. 147-164, 2015.
[28]	Z. Zhu, H. Yin, Y. Chai, Y. Li, and G. Qi, " A novel multi-modality
image fusion method based on image decomposition and sparse
representation, " Information Sciences, vol. 432, pp. 516-529, 2018.
52	

[29]	S. Singh and R.S. Anand, " Multimodal medical image sensor

using hybrid layer decomposition with CNN-based feature

vol. 23, no. 12, pp. 1882-1886, 2016.
[44]	M. Morup and M. Schmidt, " Transformation invariant sparse
coding, " in Proc. IEEE Int. Workshop Mach. Learn. Signal Process.,
pp. 1-6, 2011.
[45]	A. Vishwakarma and M.K. Bhuyan, " Image fusion using
adjustable non-subsampled shearlet transform, " IEEE Trans.
Instrum. Meas., vol. 68, no. 9, pp. 3367-3378, 2019.
[46]	Y. Liu, X. Chen, R. Ward, and Z. Wang, " Medical image fusion
via convolutional sparsity based morphological component

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