Super-Resolution: Computational and Deep Learning-Based Approaches

Presentation by Majid Rabbani and Prasanna Reddy Pulakurthi on 26 April 2023, as part of the Society for Imaging Science and Technology (IS&T) Rochester NY chapter seminar series.

Super-resolution refers to obtaining an image at a resolution higher than that of the camera sensor. Super-resolution can be applied either to a single low-resolution image or to a single frame within a low-resolution captured sequence. The approaches can be either computational-based (using physical modeling of the capture process, subpixel motion estimation and image registration, and regularized spatially variant deblurring) or example-based using machine learning and deep convolutional networks. This presentation provides a brief overview of the history and the evolution of the field while addressing its challenges and future directions.