Multilevel Features Convolutional Neural Network for Multifocus Image Fusion

Very Deep Convolutional Networks for Large-Scale Image Recognition

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ImageNet classification with deep convolutional neural networks

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Densely Connected Convolutional Networks

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Image Fusion With Guided Filtering

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Multisensor Image Fusion Using the Wavelet Transform

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Image fusion meets deep learning: A survey and perspective

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Multi-focus image fusion: A Survey of the state of the art

Liu, Y., Wang, L., Cheng, J., Li, C., & Chen, X. (2020) · Information Fusion · doi:10.1016/j.inffus.2020.06.013 · Cited by 326

Classification Saliency-Based Rule for Visible and Infrared Image Fusion

Xu, H., Zhang, H., & Ma, J. (2021) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2021.3100986 · Cited by 297

Medical image fusion method by deep learning

Li, Y., Zhao, J., Lv, Z., & Li, J. (2021) · International Journal of Cognitive Computing in Engineering · doi:10.1016/j.ijcce.2020.12.004 · Cited by 280

Current advances and future perspectives of image fusion: A comprehensive review

Karim, S., Tong, G., Li, J., Qadir, A., Farooq, U., & Yu, Y. (2022) · Information Fusion · doi:10.1016/j.inffus.2022.09.019 · Cited by 290

DRPL: Deep Regression Pair Learning for Multi-Focus Image Fusion

Li, J., Guo, X., Lu, G., Zhang, B., Xu, Y. D., Wu, F., & Zhang, D. D. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.2976190 · Cited by 240

Deep Learning-based Multi-focus Image Fusion: A Survey and A Comparative Study

Zhang, X. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3078906 · Cited by 212

Infrared and Visible Image Fusion via Texture Conditional Generative Adversarial Network

Yang, Y., Liu, J., Huang, S., Wan, W., Wen, W., & Guan, J. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3054584 · Cited by 183

ZMFF: Zero-shot multi-focus image fusion

Hu, X., Jiang, J., Liu, X., & Ma, J. (2022) · Information Fusion · doi:10.1016/j.inffus.2022.11.014 · Cited by 141

Multi-focus image fusion techniques: a survey

Bhat, S., & Koundal, D. (2021) · Artificial Intelligence Review · doi:10.1007/s10462-021-09961-7 · Cited by 77

Injected Infrared and Visible Image Fusion via $L_{1}$ Decomposition Model and Guided Filtering

Yan, H., Zhang, J., & Zhang, X. (2022) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2022.3151472 · Cited by 73

SMFuse: Multi-Focus Image Fusion Via Self-Supervised Mask-Optimization

Ma, J., Le, Z., Tian, X. S., & Jiang, J. (2021) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2021.3063872 · Cited by 72

Multi-focus image fusion with deep residual learning and focus property detection

Liu, Y., Wang, L., Li, H., & Chen, X. (2022) · Information Fusion · doi:10.1016/j.inffus.2022.06.001 · Cited by 65

Depth-Distilled Multi-Focus Image Fusion

Zhao, F., Zhao, W., Lu, H., Liu, Y., Yao, L., & Liu, Y. (2021) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3134565 · Cited by 50

Side-Scan Sonar Image Segmentation Based on Multi-Channel Fusion Convolution Neural Networks

Wang, Z., Guo, J., Huang, W., & Zhang, S. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3149841 · Cited by 50

Green Fluorescent Protein and Phase Contrast Image Fusion Via Detail Preserving Cross Network

Tang, W., Liu, Y., Cheng, J., Li, C., & Chen, X. (2021) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2021.3083965 · Cited by 47

Dual-Stream Convolutional Neural Network With Residual Information Enhancement for Pansharpening

Yang, Y., Tu, W., Huang, S., Lu, H., Wan, W., & Gan, L. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3098752 · Cited by 40

Multi-focus image fusion based on quad-tree decomposition and edge-weighted focus measure

Wang, J., Qu, H., Wei, Y., Xie, M., Xu, J. Y., & Zhang, Z. (2022) · Signal Processing · doi:10.1016/j.sigpro.2022.108590 · Cited by 35

Attentive Composite Residual Network for Robust Rain Removal from Single Images

Que, Y., Li, S., & Lee, H. J. (2020) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.3019680 · Cited by 32

From Conventional Approach to Machine Learning and Deep Learning Approach: An Experimental and Comprehensive Review of Image Fusion Techniques

Choudhary, G., & Sethi, D. (2022) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-022-09833-5 · Cited by 33

Green Fluorescent Protein and Phase-Contrast Image Fusion via Generative Adversarial Networks

Tang, W., Liu, Y., Zhang, C., Cheng, J., Peng, H., & Chen, X. (2019) · Computational and Mathematical Methods in Medicine · doi:10.1155/2019/5450373 · Cited by 31

Latent Representation Learning Model for Multi-Band Images Fusion via Low-Rank and Sparse Embedding

Wang, B., Niu, H., Zeng, J., Bai, G., Lin, S., & Wang, Y. (2020) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.3020695 · Cited by 31

Structural Similarity Loss for Learning to Fuse Multi-Focus Images

Yan, X., Gilani, S. Z., Qin, H., & Mian, A. S. (2020) · Sensors · doi:10.3390/s20226647 · Cited by 30

PCDRN: Progressive Cascade Deep Residual Network for Pansharpening

Yang, Y., Tu, W., Huang, S., & Lu, H. (2020) · Remote Sensing · doi:10.3390/rs12040676 · Cited by 30

Multiscale Feature Interactive Network for Multifocus Image Fusion

Liu, Y., Wang, L., Cheng, J., & Chen, X. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3124058 · Cited by 30

Multi-Focus Image Fusion Based on Residual Network in Non-Subsampled Shearlet Domain

Liu, S., Wang, J., Lu, Y., Hu, S., Ma, X., & Wu, Y. (2019) · IEEE Access · doi:10.1109/access.2019.2947378 · Cited by 28

Multi-focus image fusion based on fractional order differentiation and closed image matting

Zhang, X., He, H., & Zhang, J. (2022) · ISA Transactions · doi:10.1016/j.isatra.2022.03.003 · Cited by 27

Learning Stereo High Dynamic Range Imaging From A Pair of Cameras With Different Exposure Parameters

Chen, Y., Jiang, G., Yu, M., Yang, Y., & Ho, Y. (2020) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2020.3001398 · Cited by 26

Visual-simulation region proposal and generative adversarial network based ground military target recognition

Meng, F., Li, Y., Shao, F., Yuan, G.-H., & Dai, J. (2021) · Defence Technology · doi:10.1016/j.dt.2021.07.001 · Cited by 24

Multimodal biomedical image fusion method via rolling guidance filter and deep convolutional neural networks

Fu, J., Li, W., Ouyang, A., & He, B. (2021) · Optik · doi:10.1016/j.ijleo.2021.166726 · Cited by 24

Fusion2Void: Unsupervised Multi-Focus Image Fusion Based on Image Inpainting

Lin, H., Lin, Y., Xia, J., Fan, L., Li, F., Wang, Y., & Ding, X. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3502200 · Cited by 21

Image fusion algorithm based on unsupervised deep learning-optimized sparse representation

An, F.-P., Ma, X., & Bai, L. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.103140 · Cited by 21

Multi-focus Image Fusion: A BenchmarkPreprint

Zhang, X. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.01116 · Cited by 19

A multi-focus image fusion framework based on multi-scale sparse representation in gradient domain

Wang, Y., Li, X., Zhu, R., Wang, Z., Feng, Y., & Zhang, X. (2021) · Signal Processing · doi:10.1016/j.sigpro.2021.108254 · Cited by 18

Integrated MPCAM: Multi-PSF learning for large depth-of-field computational imaging

Kou, T., Zhang, Q., Zhang, C., He, T., & Shen, J. (2022) · Information Fusion · doi:10.1016/j.inffus.2022.09.005 · Cited by 16

Focus Relationship Perception for Unsupervised Multi-Focus Image Fusion

Liu, J., Shutao Li, A., Dian, R., & Ze, S. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3347099 · Cited by 16

MSIMCNN: Multi-scale inception module convolutional neural network for multi-focus image fusion

Gao, W., Yu, L., Tan, Y., & Yang, P. (2022) · Applied Intelligence · doi:10.1007/s10489-022-03160-9 · Cited by 16

Mathematical modeling and simulation of multi-focus image fusion techniques using the effect of image enhancement criteria: a systematic review and performance evaluation

Choudhary, G., & Sethi, D. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10487-3 · Cited by 15

Decoupling Image Deblurring Into Twofold: A Hierarchical Model for Defocus Deblurring

Liang, P., Jiang, J., Liu, X., & Ma, J. (2024) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2024.3443732 · Cited by 16

A Medical Image Fusion Method Based on SIFT and Deep Convolutional Neural Network in the SIST Domain

Wang, L., Chang, C., Liu, Z., Huang, J., Liu, C., & Liu, C. (2021) · Journal of Healthcare Engineering · doi:10.1155/2021/9958017 · Cited by 14

Multimodal image fusion based on global-regional-local rule in NSST domain

Zhang, Z., Xi, X., Luo, X., Jiang, Y., Dong, J., & Wu, X. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09647-2 · Cited by 13

DoF-Extended Zoomed-In Monitoring System With High-Frame-Rate Focus Stacking and High-Speed Pan-Tilt Adjustment

Zhang, T., Li, Z., Wang, Q., Shimasaki, K., Ishii, I., & Namiki, A. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2024.3351202 · Cited by 13

MCRD‐Net: An unsupervised dense network with multi‐scale convolutional block attention for multi‐focus image fusion

Zhou, D. X., Jin, X., Jiang, Q., Cai, L., Lee, S., & Yao, S. (2022) · IET Image Processing · doi:10.1049/ipr2.12430 · Cited by 12

Automated placental abruption identification using semantic segmentation, quantitative features, SVM, ensemble and multi-path CNN

Asadpour, V., Puttock, E. J., Getahun, D., Fassett, M. J., & Xie, F. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e13577 · Cited by 11

CFNet: Context fusion network for multi‐focus images

Zhang, K., Wu, Z., Yuan, X., & Zhao, C. (2021) · IET Image Processing · doi:10.1049/ipr2.12363 · Cited by 11

Multi-Focus Image Fusion: A Systematic Literature Review

Basu, S., Singhal, S., & Singh, D. (2025) · SN Computer Science · doi:10.1007/s42979-025-03678-y · Cited by 11

NCDCN: multi-focus image fusion via nest connection and dilated convolution network

Guan, Z., Wang, X., Nie, R., Yu, S., & Wang, C. (2022) · Applied Intelligence · doi:10.1007/s10489-022-03194-z · Cited by 11

TPP: Deep learning based threshold post-processing multi-focus image fusion method

Fang, L., Zhao, J., Pan, Z., & Li, Y. (2023) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2023.108736 · Cited by 11

Non-Local Multi-Focus Image Fusion With Recurrent Neural Networks

Duan, Z., Zhang, T., Tan, J., & Luo, X. (2020) · IEEE Access · doi:10.1109/access.2020.3010542 · Cited by 10

GANSD: A generative adversarial network based on saliency detection for infrared and visible image fusion

Fu, Y., Liu, Z., Peng, J., Gupta, R., & Zhang, D. (2025) · Image and Vision Computing · doi:10.1016/j.imavis.2024.105410 · Cited by 9

Euclidian Norm Based Fusion Strategy for Multi Focus Images

Shihabudeen, H., & Rajeesh, J. (2021) · International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS) · doi:10.1109/access51619.2021.9563338 · Cited by 9

Fast-armored target detection based on multi-scale representation and guided anchor

Meng, F., Wang, X., Shao, F., Wang, D., & Hu, X.-D. (2019) · Defence Technology · doi:10.1016/j.dt.2019.11.009 · Cited by 9

Multi-level receptive field feature reuse for multi-focus image fusion

Jiang, L., Fan, H., & Li, J. (2022) · Machine Vision and Applications · doi:10.1007/s00138-022-01345-3 · Cited by 7

Infrared-visible image fusion method based on multi-scale shearing Co-occurrence filter

Zhu, F., & Liu, W. (2023) · Infrared Physics & Technology · doi:10.1016/j.infrared.2023.105009 · Cited by 7

MHDBN: Mamba-based hybrid dual-branch network for multi-focus image fusion

Wu, P., & Tang, J. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.107916 · Cited by 6

Cross-Modal Learning via Adversarial Loss and Covariate Shift for Enhanced Liver Segmentation

Özkan, S., Selver, M. A., Baydar, B., Kavur, A. E., Candemir, C., & Akar, G. B. (2024) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2024.3369868 · Cited by 6

Inverting the Imaging Process by Learning an Implicit Camera Model

Huang, X., Zhang, Q., Feng, Y., Li, H., & Wang, Q. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.02055 · Cited by 6

Multi-focus image fusion via adaptive fractional differential and guided filtering

Li, X., Chen, H., Li, Y., & Peng, Y. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16785-w · Cited by 5

Multi-focused image fusion algorithm based on multi-scale hybrid attention residual network

Liu, T., Chen, M., Duan, Z., & Cui, A. (2024) · PLoS ONE · doi:10.1371/journal.pone.0302545 · Cited by 5

Infrared and visible image fusion based on relative total variation and multi feature decomposition

Xu, X., Ren, L., Liang, X., & Liu, X. (2024) · Infrared Physics & Technology · doi:10.1016/j.infrared.2024.105667 · Cited by 5

Infrared and visible image fusion using salient decomposition based on a generative adversarial network

Chen, L., & Han, J. (2021) · Applied Optics · doi:10.1364/ao.427245 · Cited by 5

LIALFP: Multi-band images synchronous fusion model based on latent information association and local feature preserving

Wang, B., Zhao, Q., Bai, G., Zeng, J., Xie, S., & Wen, L. (2021) · Infrared Physics & Technology · doi:10.1016/j.infrared.2021.103975 · Cited by 5

A Fusion Method in Frequency Domain for Multi-Wavelength Transmission Image

Liu, F., Li, G., Yan, W., He, G., Yang, S., & Lin, L. (2019) · IEEE Access · doi:10.1109/access.2019.2954694 · Cited by 5

Multi-energy X-ray images fusion method based on fuzzy entropy and sparse representation for complex castings

Zhao, R., Liu, Y., Zhao, Z., Xia, Z., Zhang, P., & Gui, Z. (2021) · NDT & E International · doi:10.1016/j.ndteint.2021.102535 · Cited by 5

FASO-C: A rapid visualization technique based on optimized fusion with crossover-based atom search for multi-band imagery

Joshi, S., Kumar, R., Rai, V., Rai, P. K., Singhal, M., & Dwivedi, A. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.123609 · Cited by 5

Deep learning model for patient emotion recognition using EEG-tNIRS data

Raparthi, M., Mitta, N. R., Dunka, V. K., Gudekota, S., Pattyam, S. P., & Nimmagadda, V. S. P. (2025) · Neuroscience Informatics · doi:10.1016/j.neuri.2025.100219 · Cited by 4

An unsupervised multi-focus image fusion method via dual-channel convolutional network and discriminator

Fang, L., Wang, X., Zhao, J., Pan, Z., Li, H., & Li, Y. (2024) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2024.104029 · Cited by 4

Thermal infrared image coloring method and evaluation method based on edge consistency

Cai, J., Tang, X., Hu, Y. G., Zhang, S., & Hao, Q. (2023) · Infrared Physics & Technology · doi:10.1016/j.infrared.2023.104946 · Cited by 3

FHFN: content and context feature hierarchical fusion networks for multi-focus image fusion

Wu, P., & Tang, J. (2024) · The Visual Computer · doi:10.1007/s00371-024-03571-4 · Cited by 3

3M: A Multi-Scale and Multi-Directional Method for Multi-Focus Image Fusion

Wei, B., Feng, X., & Wang, W. (2021) · IEEE Access · doi:10.1109/access.2021.3068770 · Cited by 3

The Fusion of Multi-Focus Images Based on the Complex Shearlet Features-Motivated Generative Adversarial Network

Wang, L., Liu, Z., Huang, J., Liu, C., Zhang, L.-B., & Liu, C. (2021) · Journal of Advanced Transportation · doi:10.1155/2021/5439935 · Cited by 3

A new multi-focus image fusion framework based on focus measures

Kahol, A., & Bhatnagar, G. (2021) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc52423.2021.9659111 · Cited by 3

GBGCN: Adaptive granular-ball graph representation and clarity-aware GCN for multi-focus image fusion

Xu, Z., Zhai, H., Zeng, Z., Lin, B., & Deng, M. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.115271 · Cited by 2

A universal adversarial example generation method for object detection system coupled with multi-focus image fusion model

Jin, X., Li, B., Gao, X., Lin, X., Sun, H., Wang, Y., Lee, S., & Jiang, Q. (2026) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-026-03018-3 · Cited by 2

A multi‐focus image fusion network deployed in smart city target detection

Zhao, H., Guo, S., Jeon, G., & Yang, X. (2024) · Expert Systems · doi:10.1111/exsy.13662 · Cited by 2

Infrared and visible image fusion using two-layer generative adversarial network

Chen, L., Han, J. W., & Tian, F. (2021) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-210041 · Cited by 2

Efficient Multi-focus Image Fusion Using Parameter Adaptive Pulse Coupled Neural Network Based Consistency Verification

Yang, B. F., & Chen, Q. (2022) · Sensing and Imaging · doi:10.1007/s11220-022-00391-5 · Cited by 2

Multi-focus Image Fusion Based on Multiple CNNs in NSCT Domain

Wang, W., Wang, X., Ma, X., & Liu, H. (2020) · doi:10.1145/3449301.3449314 · Cited by 1

Multi-focus Image Fusion Methods: A Review

Kaur, R., & Singh, S. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-47221-3_10 · Cited by 1

PTIFNet: Pseudo-Twin network for multi-focus image fusion

Wu, P., & Tang, J. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-19470-8 · Cited by 1

Two‐stage progressive residual learning network for multi‐focus image fusion

Wang, H., Hua, Z., & Li, J. (2021) · IET Image Processing · doi:10.1049/ipr2.12383 · Cited by 1

MCNN: Conditional focus probability learning to multi‐focus image fusion via mutually coupled neural network

Wang, C., Pu, Y., Wang, X., Ma, C., & Nie, R. (2023) · IET Image Processing · doi:10.1049/ipr2.12805 · Cited by 1

SFPN: segmentation-based feature pyramid network for multi-focus image fusion

Wu, P., Jiang, L., Li, Y., Fan, H., & Li, J. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-15342-9 · Cited by 1

Hybrid Optimization for High Aspect Ratio Wings with Convolutional Neural Networks and Squirrel Optimization Algorithm

Li, P. (2024) · Scalable Computing Practice and Experience · doi:10.12694/scpe.v25i1.2267 · Cited by 1

Derin evrişimli sinir ağı modellerinin açık kaynak kodlu yazılım platformlarında tasarımının değerlendirilmesi

SELÇUK, H., Akıncı, T. Ç., & Şeker, S. (2021) · İstanbul Sabahattin Zaim Üniversitesi Fen Bilimleri Enstitüsü Dergisi · doi:10.47769/izufbed.859937 · Cited by 1

Preference Learning to Multifocus Image Fusion via Generative Adversarial Network

He, M., Yu, S., Nie, R., & Wang, C. (2021) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2021.3126330 · Cited by 1

MSTCNN: A Transformer with multi-scale convolutional neural network for multi-focus image fusionPreprint

Zhai, H., Chen, Y., Zeng, Z., Luo, N., & Li, Q. (2023) · Research Square · doi:10.21203/rs.3.rs-3303519/v1 · Cited by 1

Superpixel-Based Multi-focus Image Fusion

Lai, K.-N., & Leou, J.-J. (2021) · Transactions on computational science and computational intelligence · doi:10.1007/978-3-030-71051-4_17

CFFusion: Cross Framework for Multi-focus Image Fusion

Wang, C., Nie, R., Wang, X., & Yu, S. (2021) · IEEE International Conference on Computer and Communications (ICCC) · doi:10.1109/iccc54389.2021.9674721

Mcnn: Conditional Focus Probability Learning to Multi-Focus Images Via Mutually Coupled Neural NetworkPreprint

Nie, R., wang, C., Cao, J., Ma, C., & Yu, S. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4001587

2019 Index IEEE Transactions on Computational Imaging Vol. 5

(2019) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2019.2959176

A fusion approach to multi-focus images using residual network

Markose, N., & Shihabudeen, H. (2023) · AIP conference proceedings · doi:10.1063/5.0107297

CT and MRI Fusion with Anisotropic Guided Filtering

Huang, Y., Li, W., Wang, G., Qiao, X., & Chen, H. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10448476

Multi-focus image fusion algorithm based on region detection and ACS network

Lin, M., & Li, W. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-19244-2

Automatic Machine Learning based Real Time Multi-Tasking Image Fusion

Karim, S., Tong, G., Li, J., Yu, X., Hao, J., & Yu, Y. (2024) · International Conference on Machine Learning and Computing (ICMLC) · doi:10.1145/3651671.3651683

Multi-focus image fusion algorithm based on adaptive connection and hybrid convolution attention

Qi, Y., Liu, H., & Ji, X. (2025) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2025.110236

A Comprehensive Survey on Emerging Trends in Image Fusion With Real World Applications

Bhutto, J. A., Rahman, Z.-U., Aamir, M., Nabi, A. U., Jumani, A. K., & Kamlesh, K. (2025) · Advances in medical diagnosis, treatment, and care (AMDTC) book series · doi:10.4018/979-8-3693-9816-6.ch001

Robust color multi-focus image fusion using quaternion sparse representation and spatial information

Liu, W., Li, W., Xia, Z., & Zhu, F. P. (2025) · AIMS Electronics and Electrical Engineering · doi:10.3934/electreng.2025023

EDFusion: Edge-guided attention and dynamic receptive field with dense residual for multi-focus image fusion

Zhai, H., Xu, Z., Zeng, Z., Yu, L., & Lin, B. (2025) · Image and Vision Computing · doi:10.1016/j.imavis.2025.105763

Multifocus image fusion method based on a convolutional neural network

Zhai, H., & Zhuang, Y. (2019) · Journal of Electronic Imaging · doi:10.1117/1.jei.28.2.023018 · Cited by 4

Multifocus Image Fusion Method Based on Convolutional Deep Belief Network

Zhai, H., & Zhuang, Y. (2020) · IEEJ Transactions on Electrical and Electronic Engineering · doi:10.1002/tee.23271 · Cited by 1

Image Segmentation-Based Multi-Focus Image Fusion Through Multi-Scale Convolutional Neural Network

Du, C., & Gao, S. (2017) · IEEE Access · doi:10.1109/access.2017.2735019 · Cited by 192

Multifocus image fusion using convolutional neural network

Yu, W., Yang, X., Çelik, T., Sushkova, O. S., & Albertini, M. K. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-08945-z · Cited by 13

Multi-focus image fusion based on fully convolutional networks

Guo, R., Shen, X., Dong, X., & Zhang, X. (2020) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1900336 · Cited by 13