RV-TMO: Large-Scale Dataset for Subjective Quality Assessment of Tone Mapped Images

Tone mapping operators (TMO) are functions that map high dynamic range (HDR) images to a standard dynamic range (SDR), while aiming to preserve the perceptual cues of a scene that govern its visual quality. Despite the increasing number of studies on quality assessment of tone mapped images, current subjective quality datasets have relatively small numbers of images and subjective opinions. Moreover, existing challenges in transferring laboratory experiments to crowdsourcing platforms put a barrier for collecting large-scale datasets through crowdsourcing. We address these challenges and propose the RealVision-TMO (RV-TMO), a large-scale tone mapped image quality dataset. RV-TMO contains 250 unique HDR images, their tone mapped versions obtained using four TMOs and pairwise comparison results from seventy unique observers for each pair. This dataset is published as part of the Journal paper titled as " RV-TMO: Large-Scale Dataset for Subjective Quality Assessment of Tone Mapped Images". If you are using this dataset in your work, please cite the paper below: @ARTICLE{9872141, author={Ak, Ali and Goswami, Abhishek and Hauser, Wolf and Le Callet, Patrick and Dufaux, Frederic}, journal={IEEE Transactions on Multimedia}, title={RV-TMO: Large-Scale Dataset for Subjective Quality Assessment of Tone Mapped Images}, year={2022}, pages={1-12}, doi={10.1109/TMM.2022.3203211}}