1. Introduction  
2. Taxonomy  
3. Motivation to perform image augmentation  
3.1. Challenges  
3.2. Vicinity distribution  
4. Model-free image augmentation  
4.1. Geometric transformation  
4.2. Multiple-image augmentation  
5. Model-based image augmentation  
5.1. Unconditional image generation  
5.2. Label-conditional image generation  
5.3. Image-conditional image generation  
6. Optimizing policy-based image augmentation  
6.1. Reinforcement learning-based  
7. Discussions  
8. Conclusion