Modern High Dynamic Range Imaging at the Time of Deep Learning

F.Banterle and A.Artusi

Modern High Dynamic Range Imaging at the Time of Deep Learning

PDF DOI

@inproceedings {10.2312:egt.20231033,
booktitle = {Eurographics 2023 – Tutorials},
editor = {Serrano, Ana and Slusallek, Philipp},
title = {{Modern High Dynamic Range Imaging at the Time of Deep Learning}},
author = {Banterle, Francesco and Artusi, Alessandro},
year = {2023},
publisher = {The Eurographics Association},
ISSN = {1017-4656},
ISBN = {978-3-03868-212-7},
DOI = {10.2312/egt.20231033}
}

In this tutorial, we introduce how the High Dynamic Range (HDR) imaging field has evolved in this new era where machine
learning approaches have become dominant. The main reason for this success is that the use of machine learning and deep
learning has automatized many tedious tasks achieving high-quality results overperforming classic methods. After an introduction to classic HDR imaging and its open problem, we will summarize the main approaches for merging of multiple exposures,
single image reconstructions or inverse tone mapping, tone mapping, and display visualization.