Conference paper
An objective method for High Dynamic Range source content selection
With the aim of improving the immersive experience of the end user, High Dynamic Range (HDR) imaging has been gaining popularity. Therefore, proper validation and performance benchmarking of HDR processing algorithms is a key step towards standardization and commercial deployment. A crucial component of such validation studies is the selection of a challenging and balanced set of source (reference) HDR content.
In order to facilitate this, we present an objective method based on the premise that a more challenging HDR scene encapsulates higher contrast, and as a result will show up more visible errors on contrast reduction. This information is subsequently analyzed via fuzzy clustering to enable a probabilistic interpretation.
To evaluate the proposed approach, we performed an experimental study on a large set of publicly available HDR images.
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 2014 |
| Pages: | 13-18 |
| Proceedings: | 6th International Workshop on Quality of Multimedia Experience |
| ISBN: | 1479965367 , 1479965375 , 9781479965366 and 9781479965373 |
| Types: | Conference paper |
| DOI: | 10.1109/QoMEX.2014.6982279 |
| ORCIDs: | Mantel, Claire and Forchhammer, Søren |
Algorithm design and analysis Communication, Networking and Broadcast Technologies Computing and Processing Conferences Dynamic range High Dynamic Range (HDR) Imaging Multimedia communication Probabilistic logic Signal Processing and Analysis Visualization clustering content selection
HDR processing algorithms HDR scene commercial deployment contrast reduction fuzzy clustering fuzzy set theory high dynamic range source content selection image enhancement pattern clustering performance benchmarking probabilistic interpretation probability publicly available HDR images standardization
