基于深度学习的多聚焦图像融合(Multi-Focus Image Fusion)论文及代码整理

基于深度学习的多聚焦图像融合(Multi-Focus Image Fusion)论文及代码整理

首先附上近期整理基于深度学习的图像融合论文的思维导图

本篇博客主要整理基于深度学习的多曝光图像融合的论文和代码
图像融合系列博客还有：

1. 图像融合论文及代码整理最全大合集参见：图像融合论文及代码整理最全大合集
2. 图像融合综述论文整理参见：图像融合综述论文整理
3. 图像融合评估指标参见：红外和可见光图像融合评估指标
4. 图像融合常用数据集整理参见：图像融合常用数据集整理
5. 通用图像融合框架论文及代码整理参见：通用图像融合框架论文及代码整理
6. 基于深度学习的红外和可见光图像融合论文及代码整理参见:基于深度学习的红外和可见光图像融合论文及代码整理
7. 更加详细的红外和可见光图像融合代码参见：红外和可见光图像融合论文及代码整理
8. 基于深度学习的多曝光图像融合论文及代码整理参见：基于深度学习的多曝光图像融合论文及代码整理
9. 基于深度学习的多聚焦图像融合论文及代码整理参见：基于深度学习的多聚焦图像融合(Multi-focus Image Fusion)论文及代码整理
10. 基于深度学习的全色图像锐化论文及代码整理参见：基于深度学习的全色图像锐化(Pansharpening)论文及代码整理
11. 基于深度学习的医学图像融合论文及代码整理参见：基于深度学习的医学图像融合(Medical image fusion)论文及代码整理
12. 彩色图像融合参见: 彩色图像融合
13. SeAFusion:首个结合高级视觉任务的图像融合框架参见：SeAFusion:首个结合高级视觉任务的图像融合框架

基于卷积神经网络的图像融合框架

1. Multi-focus image fusion with a deep convolutional neural network [CNN(IF 2017)] [Paper] [Code]

2. Ensemble of CNN for multi-focus image fusion [ECNN(IF 2019)] [Paper] [Code]

3. Multilevel features convolutional neural network for multifocus image fusion [MLFCNN(TCI 2019)] [Paper]

4. DRPL: Deep Regression Pair Learning for Multi-Focus Image Fusion [DRPL(TIP 2020)] [Paper] [Code]

5. An α-Matte Boundary Defocus Model-Based Cascaded Network for Multi-Focus Image Fusion [MMF-Net(TIP 2020)] [Paper] [Code]

6. Towards Reducing Severe Defocus Spread Effects for Multi-Focus Image Fusion via an Optimization Based Strategy [MFF-SSIM(TCI 2020)] [Paper] [Code]

7. Structural Similarity Loss for Learning to Fuse Multi-Focus Images [MFNet(Sensors 2020)] [Paper]

8. Global-Feature Encoding U-Net (GEU-Net) for Multi-Focus Image Fusion [GEU-Net(TIP 2021)] [Paper] [Code]

9. DTMNet: A Discrete Tchebichef Moments-Based Deep Neural Network for Multi-Focus Image Fusion [DTMNet(ICCV 2021)] [Paper]

10. SMFuse: Multi-Focus Image Fusion Via Self-Supervised Mask-Optimization [SMFuse(TCI 2021)] [Paper] [Code]

11. Depth-Distilled Multi-focus Image Fusion [D2MFIF(TMM 2021)] [Paper] [Code]

12. SESF-Fuse: an unsupervised deep model for multi-focus image fusion [SESF-Fuse(NCAA 2021)] [Paper] [Code]

基于生成对抗网络的图像融合框架

1. FuseGAN: Learning to fuse multi-focus image via conditional generative adversarial network [FuseGAN(TMM 2019)] [Paper]

2. A generative adversarial network with adaptive constraints for multi-focus image fusion [ACGAN(NCA 2020)] [Paper] [Code]

3. MFF-GAN: An unsupervised generative adversarial network with adaptive and gradient joint constraints for multi-focus image fusion [MFF-GAN(IF 2021)] [Paper] [Code]

4. MFIF-GAN: A new generative adversarial network for multi-focus image fusion [MFIF-GAN(SPIC 2021)] [Paper] [Code]

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