\dm_csml_event_details UCL ELLIS

Lucas-Kanade Reloaded End-to-End Super-Resolution from Raw Image Bursts


Speaker

Julien Mairal

Affiliation

Inria Grenoble, Thoth team

Date

Friday, 01 April 2022

Time

14:00-15:00

Location

Zoom

Link

https://ucl.zoom.us/j/97245943682

Event series

Jump Trading/ELLIS CSML Seminar Series

Abstract

This presentation addresses the problem of reconstructing a high-resolution image from multiple lower-resolution snapshots captured from slightly different viewpoints in space and time. Key challenges for solving this super-resolution problem include (i) aligning the input pictures with sub-pixel accuracy, (ii) handling raw (noisy) images for maximal faithfulness to native camera data, and (iii) designing and learning an image prior (regularizer) well suited to the task. We address these three challenges with a hybrid algorithm building on the insight that aliasing is an ally in this setting, with parameters that can be learned end to end, while retaining the interpretability of classical approaches to inverse problems. The effectiveness of our approach is demonstrated on synthetic and real image bursts, setting a new state of the art on several benchmarks and delivering excellent qualitative results on real raw bursts captured by smartphones and prosumer cameras. This is a joint work with Bruno Lecouat and Jean Ponce.

Biography