Name
Abstract | ||
|---|---|---|
Existing tone mapping operators (TMOs) provide good results in well-lit scenes, but often perform poorly on im-ages in low light conditions. In these scenes, noise is prevalent and gets amplified by TMOs, as they confuse contrast created by noise with contrast created by the scene. This paper presents a principled approach to produce tone mapped images with less visible noise. For this purpose, we leverage established models of camera noise and human contrast perception to design two new quality scores: contrast waste and contrast loss, which measure image quality as a function of contrast allocation. To produce tone mappings with less visible noise, we apply these scores in two ways: first, to automatically tune the parameters of existing TMOs to reduce the amount of noise they produce; and second, to propose a new noise-aware tone curve |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICCPHOT.2015.7168364 | ICCP |
Field | DocType | ISSN |
Computer vision,Colors of noise,Noise measurement,Visualization,Computer science,Image processing,Image quality,Image noise,Tone mapping,Artificial intelligence,Perception | Conference | 2164-9774 |
Citations | PageRank | References |
2 | 0.37 | 13 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miguel Granados | 1 | 162 | 7.41 |
| Tunç O. Aydin | 2 | 242 | 14.94 |
| J. Rafael Tena | 3 | 92 | 5.25 |
| Jean-françois Lalonde | 4 | 590 | 37.69 |
| Christian Theobalt | 5 | 3211 | 159.16 |