Taesu Kim, a Ph.D. student of color lab, gave an oral presentation entitled as, “Illuminant Estimation Through Reverse Calibration of an Auto White-Balanced Image That Contains Displays” at CIC27 in Paris. He proposed reverse algorithm to estimate original illuminants from automatically calibrated digital images. In particular, he used the color of smartphone display as a calibration target for the reversed estimation. The result shows that algorithm works at satisfactory level under the low purity illuminants that we experience in our daily lives.
This study proposes an illuminant estimation method that reproduces the original illuminant of a scene using a mobile display as a target. The original lighting environment of an auto white-balancing (AWB) photograph is obtained through reverse calibration, using the white point of a display in the photograph. This reproduces the photograph before AWB processed, and we can obtain the illuminant information using Gray World computation. The study consists of two sessions. In Session 1, we measured the display’s white points under varying illuminants to prove that display colors show limited changes under any light conditions. Then, in Session 2, we generated the estimations and assessed the performance of display-based illuminant estimation by comparing the result with the optically measured values in the real situation. Overall, the proposed method is a satisfactory way to estimate the less chromatic illuminants under 6300 K that we experience as indoor light in our daily lives.