Fast Fourier Color Constancy

Jonathan T. Barron, Yun-Ta Tsai; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, pp. 886-894

Abstract


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 Material


[pdf] [Supp] [arXiv]
[bibtex]
@InProceedings{Barron_2017_CVPR,
author = {Barron, Jonathan T. and Tsai, Yun-Ta},
title = {Fast Fourier Color Constancy},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {July},
year = {2017}
}