Time-Aware Auto White Balance in Mobile Photography
Journal:
arXiv
Published Date:
Apr 8, 2025
Abstract
Cameras rely on auto white balance (AWB) to correct undesirable color casts
caused by scene illumination and the camera's spectral sensitivity. This is
typically achieved using an illuminant estimator that determines the global
color cast solely from the color information in the camera's raw sensor image.
Mobile devices provide valuable additional metadata-such as capture timestamp
and geolocation-that offers strong contextual clues to help narrow down the
possible illumination solutions. This paper proposes a lightweight illuminant
estimation method that incorporates such contextual metadata, along with
additional capture information and image colors, into a compact model (~5K
parameters), achieving promising results, matching or surpassing larger models.
To validate our method, we introduce a dataset of 3,224 smartphone images with
contextual metadata collected at various times of day and under diverse
lighting conditions. The dataset includes ground-truth illuminant colors,
determined using a color chart, and user-preferred illuminants validated
through a user study, providing a comprehensive benchmark for AWB evaluation.
