Super-Resolution: Computational and Deep Learning-Based Approaches

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

Abstract: Super-resolution refers to obtaining an image higher than the camera sensor’s resolution. Super-resolution can be applied to a single low-resolution image or 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 field’s history and evolution while addressing its challenges and future directions.

Video file of the presentation (YouTube),

Presentation File (PDF), /burnsdigitalimaging/ISandT/ISandT%20Super-Resolution%20Rabbani%20and%20%20Pulakurthi%20.pdf