Super resolution aims to recover a plausible high resolution version of a low resolution image. The main techniques that were used to solve this problem were interpolation, enhancing linear methods and patch-based methods. Nowadays, state of the art in super resolution is Deep Convolution Neural Networks. These networks exploit low and high level image features to reconstruct perceptually realistic photos and videos.
In the field of security, super resolution could be used as preprocessing tool for tracking, face and object recognition.
Super-Resolution Ex. 01
Super-Resolution Ex. 02
Visual Computing Lab
The focus of the Visual Computing Laboratory is to develop new algorithms and architectures for applications in the areas of 3D processing, image/video processing, computer vision, pattern recognition, bioinformatics and medical imaging.