Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.21831 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913862450675712 |
|---|---|
| author | Chen, Bowen Lee, Cheng-han Chen, Yixu Shang, Zaixi Wei, Hai Bovik, Alan C. |
| author_facet | Chen, Bowen Lee, Cheng-han Chen, Yixu Shang, Zaixi Wei, Hai Bovik, Alan C. |
| contents | We introduce HDRSDR-VQA, a large-scale video quality assessment dataset designed to facilitate comparative analysis between High Dynamic Range (HDR) and Standard Dynamic Range (SDR) content under realistic viewing conditions. The dataset comprises 960 videos generated from 54 diverse source sequences, each presented in both HDR and SDR formats across nine distortion levels. To obtain reliable perceptual quality scores, we conducted a comprehensive subjective study involving 145 participants and six consumer-grade HDR-capable televisions. A total of over 22,000 pairwise comparisons were collected and scaled into Just-Objectionable-Difference (JOD) scores. Unlike prior datasets that focus on a single dynamic range format or use limited evaluation protocols, HDRSDR-VQA enables direct content-level comparison between HDR and SDR versions, supporting detailed investigations into when and why one format is preferred over the other. The open-sourced part of the dataset is publicly available to support further research in video quality assessment, content-adaptive streaming, and perceptual model development. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_21831 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | HDRSDR-VQA: A Subjective Video Quality Dataset for HDR and SDR Comparative Evaluation Chen, Bowen Lee, Cheng-han Chen, Yixu Shang, Zaixi Wei, Hai Bovik, Alan C. Computer Vision and Pattern Recognition We introduce HDRSDR-VQA, a large-scale video quality assessment dataset designed to facilitate comparative analysis between High Dynamic Range (HDR) and Standard Dynamic Range (SDR) content under realistic viewing conditions. The dataset comprises 960 videos generated from 54 diverse source sequences, each presented in both HDR and SDR formats across nine distortion levels. To obtain reliable perceptual quality scores, we conducted a comprehensive subjective study involving 145 participants and six consumer-grade HDR-capable televisions. A total of over 22,000 pairwise comparisons were collected and scaled into Just-Objectionable-Difference (JOD) scores. Unlike prior datasets that focus on a single dynamic range format or use limited evaluation protocols, HDRSDR-VQA enables direct content-level comparison between HDR and SDR versions, supporting detailed investigations into when and why one format is preferred over the other. The open-sourced part of the dataset is publicly available to support further research in video quality assessment, content-adaptive streaming, and perceptual model development. |
| title | HDRSDR-VQA: A Subjective Video Quality Dataset for HDR and SDR Comparative Evaluation |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2505.21831 |