1 Introduction

2 Review of supervised learning methods  
2.1 Principle of supervised learning  
2.2 Classes of parameterized functions  
2.3 Parameter optimization  
2.4 Weakly supervised learning  
2.5 Discussion and conclusion  

3 Unsupervised denoising methods  
3.1 Weighted averaging methods  
3.2 Sparsity methods  
3.3 Bayesian methods coupled with a Gaussian model  
3.4 Deep learning-based methods  

4 Normalization-equivariance property of denoising methods  
4.1 Normalization-equivariance of conventional denoisers  
4.2 The case of neural networks  
4.3 Categorizing image denoisers  

5 Conclusion