Fast Fourier Color Constancy
About
We present Fast Fourier Color Constancy (FFCC), a color constancy algorithm which solves illuminant estimation by reducing it to a spatial localization task on a torus. By operating in the frequency domain, FFCC produces lower error rates than the previous state-of-the-art by 13-20% while being 250-3000 times faster. This unconventional approach introduces challenges regarding aliasing, directional statistics, and preconditioning, which we address. By producing a complete posterior distribution over illuminants instead of a single illuminant estimate, FFCC enables better training techniques, an effective temporal smoothing technique, and richer methods for error analysis. Our implementation of FFCC runs at ~700 frames per second on a mobile device, allowing it to be used as an accurate, real-time, temporally-coherent automatic white balance algorithm.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Color Constancy | NUS-8 (three-fold cross val) | Mean Angular Error (MAE)1.99 | 31 | |
| Color Constancy | Gehler (3-fold cross validation) | Mean Error1.61 | 26 | |
| Color Constancy | ETH3D RAW | Mean Error1.08 | 19 | |
| Color Constancy | DepthAWB | Mean Error1.32 | 19 | |
| Color Constancy | NYU-v2 & Diode | Mean Angular Error2.75 | 19 |