Impact Of Loss Function On Multi-Frame Super-Resolution

Abstract

Nowadays, one of the most popular topics in image processing is super-resolution. Thisproblem is getting more actual even in security, since monitoring cameras are everywhere and inthe case of an incident, it is necessary to recognize a person from records. A lot of approaches exist,which are able to reconstruct image, and the most of them are based on deep learning. The main focusof this work is to analyze, which loss function for neural networks is more effective for real-worldimage reconstruction. For this experiment chosen architecture and dataset are used for multi-framesuper-resolution for _x0002_8 scaling.