Superresolution image processing using an invertible sparse matrix

Abstract

Superresolution image processing that can be applied when two image frames of the same scene are available so that image information from one frame can be used to enhance the image from the other frame. The superresolution image processing uses a sparse matrix generated based on a Markov random field defined over these two image frames. The sparse matrix is inverted and applied to the image data from the image frame that is being enhanced to generate a corresponding enhanced image.

Aleksandr Petiushko Александр Петюшко
Aleksandr Petiushko Александр Петюшко
Director, Head of ML Research / Adjunct Professor / PhD

Principal R&D Researcher (15+ years of experience), R&D Technical Leader (10+ years of experience), and R&D Manager (8+ years of experience). Running and managing industrial research and academic collaboration (35+ publications, 30+ patents). Inspired by theoretical computer science and how it changes the world.