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Yiqi Hu, Tianheng Zheng, Guanglu Dong, Pingyu Wang, Xing Ruan
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10.1109/iccvw54120.2021.00210 · doi-reference
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Dynamic threshold neural P systems
10.1016/j.knosys.2018.10.016 · doi-reference
ZMFF: Zero-shot multi-focus image fusion
10.1016/j.inffus.2022.11.014 · doi-reference
End-to-end learning for simultaneously generating decision map and multi-focus image fusion result
10.1016/j.neucom.2021.10.115 · doi-reference
SwinMFF: toward high-fidelity end-to-end multi-focus image fusion via swin transformer-based network
10.1007/s00371-024-03637-3 · doi-reference
SwinFusion: Cross-domain long-range learning for general image fusion via swin transformer
10.1109/jas.2022.105686 · doi-reference
IFCNN: A general image fusion framework based on convolutional neural network
10.1016/j.inffus.2019.07.011 · doi-reference
StackMFF: end-to-end multi-focus image stack fusion network
10.1007/s10489-025-06383-8 · doi-reference
MFIF-DWT-CNN: Multi-focus ımage fusion based on discrete wavelet transform with deep convolutional neural network
10.1007/s11042-023-16074-6 · doi-reference
Sesf-fuse: An unsupervised deep model for multi-focus image fusion
10.1007/s00521-020-05358-9 · doi-reference
SDNet: A versatile squeeze-and-decomposition network for real-time image fusion
10.1007/s11263-021-01501-8 · doi-reference
Dual-path deep unsupervised learning for multi-focus image fusion
10.1109/tmm.2024.3521817 · doi-reference
Unfolding coupled convolutional sparse representation for multi-focus image fusion
10.1016/j.inffus.2025.102974 · doi-reference
Multi-focus image fusion with parameter adaptive dual channel dynamic threshold neural P systems
10.1016/j.neunet.2024.106603 · doi-reference
SMFuse: Multi-focus image fusion via self-supervised mask-optimization
10.1109/tci.2021.3063872 · doi-reference
Multi-focus image fusion based on non-negative sparse representation and patch-level consistency rectification
10.1016/j.patcog.2020.107325 · doi-reference
Multi-focus image fusion with a deep convolutional neural network
10.1016/j.inffus.2016.12.001 · doi-reference
DRPL: Deep regression pair learning for multi-focus image fusion
10.1109/tip.2020.2976190 · doi-reference
FuseGAN: Learning to fuse multi-focus image via conditional generative adversarial network
10.1109/tmm.2019.2895292 · doi-reference
Multi-focus image fusion: a systematic literature review
10.1007/s42979-025-03678-y · doi-reference
A review on multi-focus image fusion using deep learning
10.1016/j.neucom.2024.129125 · doi-reference
MFIF-GAN: A new generative adversarial network for multi-focus image fusion
10.1016/j.image.2021.116295 · doi-reference
MFF-GAN: An unsupervised generative adversarial network with adaptive and gradient joint constraints for multi-focus image fusion
10.1016/j.inffus.2020.08.022 · doi-reference
Combining transformers with CNN for multi-focus image fusion
10.1016/j.eswa.2023.121156 · doi-reference
Deep learning for pixel-level image fusion: Recent advances and future prospects
10.1016/j.inffus.2017.10.007 · doi-reference
Multi-focus image fusion using a morphology-based focus measure in a quad-tree structure
10.1016/j.inffus.2012.01.007 · doi-reference
Image matting for fusion of multi-focus images in dynamic scenes
10.1016/j.inffus.2011.07.001 · doi-reference
Multifocus image fusion and restoration with sparse representation
10.1109/tim.2009.2026612 · doi-reference
Image fusion by using steerable pyramid
10.1016/s0167-8655(01)00047-2 · doi-reference