Subjective Quality Assessment of Compressed Tone-Mapped High Dynamic Range Videos
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Abstract (arXiv)
High Dynamic Range (HDR) videos are able to represent wider ranges of contrasts and colors than Standard Dynamic Range (SDR) videos, giving more vivid experiences. Due to this, HDR videos are expected to grow into the dominant video modality of the future. However, HDR videos are incompatible with existing SDR displays, which form the majority of affordable consumer displays on the market. Because of this, HDR videos must be processed by tone-mapping them to reduced bit-depths to service a broad swath of SDR-limited video consumers. Here, we analyze the impact of tone-mapping operators on the visual quality of streaming HDR videos. To this end, we built the first large-scale subjectively annotated open-source database of compressed tone-mapped HDR videos, containing 15,000 tone-mapped sequences derived from 40 unique HDR source contents. The videos in the database were labeled with more than 750,000 subjective quality annotations, collected from more than 1,600 unique human observers. We demonstrate the usefulness of the new subjective database by benchmarking objective models of visual quality on it. We envision that the new LIVE Tone-Mapped HDR (LIVE-TMHDR) database will enable significant progress on HDR video tone mapping and quality assessment in the future. To this end, we make the database freely available to the community at https://live.ece.utexas.edu/research/LIVE_TMHDR/index.html
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 14 of its 86 references that are in the map. First posted on arXiv 22 Mar 2024.
Builds on
14 of 86 references.
References · 14
- 2015Massive Online Crowdsourced Study of Subjective and Objective Picture Qualitycited by 209
- 2020Patch-VQ: 'Patching Up' the Video Quality Problemcited by 147
- 2020UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Contentcited by 140
- 2018Large-Scale Study of Perceptual Video Qualitycited by 127
- 2019Deep Tone Mapping Operator for High Dynamic Range Imagescited by 26
- 2020A Simple Model for Subject Behavior in Subjective Experimentscited by 15
- 2022Subjective Assessment of High Dynamic Range Videos Under Different Ambient Conditionscited by 13
- 2023One Transform To Compute Them All: Efficient Fusion-Based Full-Reference Video Quality Assessmentcited by 9
- 2017FSITM: A Feature Similarity Index For Tone-Mapped Imagescited by 8
- 2022FUNQUE: Fusion of Unified Quality Evaluatorscited by 8
- 2023Making Video Quality Assessment Models Robust to Bit Depthcited by 6
- 2021Deep Reformulated Laplacian Tone Mappingcited by 5
Built on by
Citing papers per year: 2024: 2; 2025: 0; 2026: 1.
3 papers.
- 2024Joint Quality Assessment and Example-Guided Image Processing by Disentangling Picture Appearance from Contentcited by 1
- 2024Cut-FUNQUE: An Objective Quality Model for Compressed Tone-Mapped High Dynamic Range Videoscited by 0
- 2026LumaFlux: Lifting 8-Bit Worlds to HDR Reality with Physically-Guided Diffusion Transformerscited by 0
- 2026LumaFlux: Lifting 8-Bit Worlds to HDR Reality with Physically-Guided Diffusion Transformers3 Apr 2026
- 2024Joint Quality Assessment and Example-Guided Image Processing by Disentangling Picture Appearance from Content20 Apr 2024
- 2024Cut-FUNQUE: An Objective Quality Model for Compressed Tone-Mapped High Dynamic Range Videos20 Apr 2024