Which tone-mapping operator is the best? A comparative study of perceptual quality
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Abstract (arXiv)
Tone-mapping operators (TMO) are designed to generate perceptually similar low-dynamic range images from high-dynamic range ones. We studied the performance of fifteen TMOs in two psychophysical experiments where observers compared the digitally generated tone-mapped images to their corresponding physical scenes. All experiments were performed in a controlled environment and the setups were designed to emphasise different image properties: in the first experiment we evaluated the local relationships among intensity-levels, and in the second one we evaluated global visual appearance among physical scenes and tone-mapped images, which were presented side by side. We ranked the TMOs according to how well they reproduce the results obtained in the physical scene. Our results show that ranking position clearly depends on the adopted evaluation criteria, which implies that, in general, these tone-mapping algorithms consider either local or global image attributes but rarely both. We conclude that a more thorough and standardized evaluation criteria are needed to study all the characteristics of TMOs, as there is ample room for improvement in future developments.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Jan 2016.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 0; 2025: 0; 2026: 1.
3 papers.
- 2021Mobile Computational Photography: A Tourcited by 62
- 2023Perceptual Tone Mapping Model for High Dynamic Range Imagingcited by 1
- 2026DRIFT: Deep Restoration, ISP Fusion, and Tone-mappingcited by 0
- 2026DRIFT: Deep Restoration, ISP Fusion, and Tone-mapping3 Apr 2026
- 2023Perceptual Tone Mapping Model for High Dynamic Range Imaging29 Sep 2023
- 2021Mobile Computational Photography: A Tour17 Feb 2021