Survey and Evaluation of Tone Mapping Operators
for HDR Video

Siggraph 2013
Gabriel Eilertsen, Jonas Unger, Robert Wanat, Rafal Mantiuk
  Media and Information Technology, Linköping University, Sweden
Bangor University, UK

Figure: The plot illustrates how different a set of representative TMOs from our evaluation, see legend, responds to the same HDR input. The plot shows the log luminance of the temporal variation of the pixels under the green square as the light bulbs are turned on and off.

This work presents a survey and a user evaluation of tone mapping operators (TMOs) for high dynamic range (HDR) video, i.e. TMOs that explicitly include a temporal model for processing of variations in the input HDR images in the time domain. The main motivations behind this work is that: robust tone mapping is one of the key aspects of HDR imaging; recent developments in sensor and computing technologies have now made it possible to capture HDR-video, and, as shown by our survey, tone mapping for HDR video poses a set of completely new challenges compared tone mapping for still HDR images. Furthermore, video tone mapping, though less studied, is highly important for multitude of applications including gaming, cameras in mobile devices, adaptive display devices and movie post-processing.
Our survey is meant to summarize the state-of-the-art in video tone-mapping and analyze differences in their response to variations in the temporal domain. In contrast to other studies, we evaluate TMOs performance according to their actual intent, such as producing the image that best resembles the real world scene, that subjectively looks best to the viewer, or fulfills a certain artistic requirement. The unique strength of this work is that we use real, high quality HDR video sequences as opposed to synthetic images or footage generated from still HDR images.
Talk Abstract (.pdf) (1.8MB)
Supplementary material describing all TMOs and the parameters used (.pdf) (19MB)
Supplementary video showing side by side examples of TMOs (.mov) (95MB)
This project was funded by the Swedish Foundation for Strategic Research (SSF) through grant IIS11-0081, Linköping University Center for Industrial Information Technology (CENIIT), and COST Action IC1005 on HDR video.


Jonas Unger 2019