Spatio-Temporal Noise Filtering using Convolutional Neural Networks with a Realistic Noise Model under Low-Light Conditions
Convolutional neural networks have in recent years been successfully employed for various image processing tasks, such as filtering noise. There are however relatively few published attempts for processing video in this way. Image processing methods on single images can be applied frame by frame, but often fail to consider continuity and flow between frames. In this master's thesis we construc
