Fast Fourier Color Constancy Jonathan T. Barron Yun-Ta Tsai
[email protected] [email protected] Abstract based techniques in computer vision, both problems reduce to just estimating the “best” illuminant from an image, and We present Fast Fourier Color Constancy (FFCC), a the question of whether that illuminant is objectively true color constancy algorithm which solves illuminant esti- or subjectively attractive is just a matter of the data used mation by reducing it to a spatial localization task on a during training. torus. By operating in the frequency domain, FFCC pro- Despite their accuracy, modern learning-based color duces lower error rates than the previous state-of-the-art by constancy algorithms are not immediately suitable as prac- 13 − 20% while being 250 − 3000× faster. This unconven- tical white balance algorithms, as practical white balance tional approach introduces challenges regarding aliasing, has several requirements besides accuracy: directional statistics, and preconditioning, which we ad- Speed - An algorithm running in a camera’s viewfinder dress. By producing a complete posterior distribution over must run at 30 FPS on mobile hardware. But a camera’s illuminants instead of a single illuminant estimate, FFCC compute budget is precious: demosaicing, face detection, enables better training techniques, an effective temporal auto exposure, etc, must also run simultaneously and in real smoothing technique, and richer methods for error analy- time. Spending more than a small fraction (say, 5 − 10%) sis. Our implementation of FFCC runs at ∼ 700 frames per of a camera’s compute budget on white balance is impracti- second on a mobile device, allowing it to be used as an ac- cal, suggesting that our speed requirement is closer to 1 − 5 curate, real-time, temporally-coherent automatic white bal- milliseconds per frame.