Adaptive Color Grading
Independent control of tonescale regions (e.g., shadows, highlights) is essential for painters, photographers and cinematographers to bring 2D images to life. In image manipulation software this is most directly addressed by color grading modules, which use intensity thresholds to segment distinct illumination regions for local manipulation. In this work we develop an open source color grading tool and use it to annotate a large dataset of video frames with tonescale region thresholds. Using these thresholds we conduct modeling experiments with strategies based on both practitioners' conventional wisdom and machine learning. Results show that K-nearest neighbors is an effective prediction...
| Authors | Trevor D. Canham, Abhijith Punnappurath, Michael S. Brown |
|---|---|
| Primary category | eess.IV |
| Published | 18 September 2026 |
| Last updated at source | 18 September 2026 |
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