[1] HE C T, LIU Q X, LI H L, et al. Multimodal medical image fusion based on IHS and PCA[J]. Procedia Engineering, 2010, 7: 280-285.
[2] DU J, LI W S, XIAO B, et al. Union Laplacian pyramid with multiple features for medical image fusion[J]. Neurocomputing, 2016, 194(6): 326-339.
[3] NAVEENADEVI R, NIRMALA S, BABU G T. Fusion of CT-PET lungs tumour images using dual tree complex wavelet transform[J]. Research Journal of Pharmaceutical, Biological and Chemical Sciences, 2017, 8: 310-316.
[4] CHAVAN S S, MAHAJAN A, TALBAR S N, et al. Nonsubsampled rotated complex wavelet transform (NSRCxWT) for medical image fusion related to clinical aspects in neurocysticercosis[J]. Computers in Biology and Medicine, 2017, 81(2): 64-78.
[5] GANASALA P, PRASAD A D. Medical image fusion based on laws of texture energy measures in stationary wavelet transform domain[J]. International Journal of Imaging Systems and Technology, 2020, 30(3): 544-557.
[6] CHAO Z, DUAN X G, JIA S F, et al. Medical image fusion via discrete stationary wavelet transform and an enhanced radial basis function neural network[J]. Applied Soft Computing, 2022, 118(2): 108542.
[7] ZHU Z Q, ZHENG M Y, QI G Q, et al. A phase congruency and local Laplacian energy based multi-modality medical image fusion method in NSCT domain[J]. IEEE Access, 2019, 7: 20811-20824.
[8] LI X H, ZHAO J. A novel multi-modal medical image fusion algorithm[J]. Journal of Ambient Intelligence and Humanized Computing, 2021, 12(2): 1995-2002.
[9] YIN M, LIU X N, LIU Y, et al. Medical image fusion with parameter-adaptive pulse coupled neural network in nonsubsampled shearlet transform domain[J]. IEEE Transactions on Instrumentation Measurements, 2019, 68(1): 49-64.
[10] ZHU R, LI X F, ZHANG X L, et al. HID: the hybrid image decomposition model for MRI and CT fusion[J]. IEEE Journal of Biomedical and Health Informatics, 2022, 26(2): 727-739.
[11] LI H, HE X, TAO D, et al. Joint medical image fusion, denoising and enhancement via discriminative low-rank sparse dictionaries learning[J]. Pattern Recognition, 2018, 79(7): 130-146.
[12] DANIEL E. Optimum wavelet-based homomorphic medical image fusion using hybrid genetic-grey wolf optimization algorithm[J]. IEEE Sensors Journal, 2018, 18(16): 6804-6811.
[13] YANG Y, WU J H, HUANG S Y, et al. Multimodal medical image fusion based on fuzzy discrimination with structural patch decomposition[J]. IEEE Journal of Biomedical and Health Informatics, 2019, 23(4): 1647-1660.
[14] ZHANG S, HUANG F Y, LIU B Q, et al. A multi-modal image fusion framework based on guided filter and sparse representation[J]. Optics and Lasers in Engineering, 2021, 137(2): 106354.
[15] ARIF M, WANG G J. Fast curvelet transform through genetic algorithm for multimodal medical image fusion[J]. Soft Computing, 2020, 24(2): 1815-1836.
[16] DU J, LI W S, TAN H L. Three-layer medical image fusion with tensor-based features[J]. Information Sciences, 2020, 525(3): 93-108.
[17] DU J, LI W S, TAN H L. Three-layer image representation by an enhanced illumination-based image fusion method[J]. IEEE Journal of Biomedical and Health Informatics, 2020, 24(4): 1169-1179.
[18] FAN F D, HUANG Y Y, WANG L, et al. A semantic-based medical image fusion approach[J]. arXiv:1906.00225, 2019.
[19] JUNG H, KIM Y, JANG H, et al. Unsupervised deep image fusion with structure tensor representations[J]. IEEE Transactions on Image Processing, 2020, 29(1): 3845-3858.
[20] XU H, MA J Y. EMFusion: an unsupervised enhanced medical image fusion network[J]. Information Fusion, 2021, 76(6): 177-186.
[21] FU J, LI W S, DU J, et al. DSAGAN: a generative adversarial network based on dual-stream attention mechanism for anatomical and functional image fusion[J]. Information Sciences, 2021, 576(10): 484-506.
[22] SHI Z H, ZHANG C W, YE D, et al. MMI-Fuse: multimodal brain image fusion with multiattention module[J]. IEEE Access, 2022, 10: 37200-37214.
[23] GOYAL S, SINGH V, RANI A, et al. Multimodal image fusion and denoising in NSCT domain using CNN and FOTGV[J]. Biomedical Signal Processing and Control, 2022, 71(1): 103214.
[24] DAUBECHIES I, HAN B, RON A, et al. Framelets: MRA-based constructions of wavelet frames[J]. Applied and Computational Harmonic Analysis, 2003, 14(1): 1-46.
[25] YIN H, GONG Y H, QIU G P. Side window filtering[C]//Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019: 8758-8766.
[26] LI X X, GUO X P, HAN P F, et al. Laplacian re-decomposition for multimodal medical image fusion[J]. IEEE Transactions on Instrumentation Measurements, 2020, 69(9): 6880-6890.
[27] LIU Y, CHEN X, WARD R, et al. Medical image fusion via convolutional sparsity based morphological component analysis[J]. IEEE Signal Processing Letters, 2019, 26(3): 485-489.
[28] LI X S, ZHOU F Q, TAN H S, et al. Multimodal medical image fusion based on joint bilateral filter and local gradient energy[J]. Information Sciences, 2021, 569(8): 302-325.
[29] HAN Y, CAI Y Z, CAO Y, et al. A new image fusion performance metric based on visual information fidelity[J]. Information Fusion, 2013, 14(2): 127-135.
[30] PIELLA G, HEIJMANS H. A new quality metric for image fusion[C]//Proceedings of the 2003 International Conference on Image Processing, 2003: 173-176.
[31] ASLANTAS V, BENDES E. A new image quality metric for image fusion: the sum of the correlations of differences[J]. AEU-International Journal of Electronics and Communications, 2015, 69(12): 1890-1896.
[32] ZHENG Y F, ESSOCK E A, HANSEN B C, et al. A new metric based on extended spatial frequency and its application to DWT based fusion algorithm[J]. Information Fusion, 2007, 8(2): 177-192. |