A Keras and Tensorflow implementation of super resolution using deep neural networks is proposed. The architecture is shown below.
- We divide the video temporal consecutive segments of 1 second duration
- We downsample the images of each segment and feed both downsampled and original image for training
- Each video segment has its own model (we called it as a micro-model because it is trained on a little data of 30 images)
- We overfit the model intentionally as there is no test phase
- Python3
- Tensorflow
- Keras
- Jupyter Notebook (optional)
Pranjal Sahu, Mallesham Dasari