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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× 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.
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Barron et al. (Sat,) studied this question.
www.synapsesocial.com/papers/6a08f03234cfc5f8bc5b7f4e — DOI: https://doi.org/10.1109/cvpr.2017.735
Jonathan T. Barron
Yun‐Ta Tsai
Chiba University
Murata (Japan)
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