TY - GEN
T1 - Data-Driven Light Source Selection for Camera Colorimetric Calibration
AU - Liu, Yuyang
AU - Wei, Minchen
AU - Qu, Xinchao
AU - Hu, Tao
N1 - Publisher Copyright:
©2024 Society for Imaging Science and Technology.
PY - 2024/10
Y1 - 2024/10
N2 - The colorimetric calibration of cameras are critical in imaging systems, with the sources used in light booths being widely used in practice. These sources, however, may not good presentations of the sources in real life, which possibly results in poor colors. In this study, we adopted a genetic algorithm and a large dataset of real light sources to identify an optimal set of sources that can better represent the sources in real life. The experiment results suggested that the identified set of sources can result in better color performance. Moreover, the selection of the sources was much less complicated in comparison to manual selections, which can be considered and implemented in practice.
AB - The colorimetric calibration of cameras are critical in imaging systems, with the sources used in light booths being widely used in practice. These sources, however, may not good presentations of the sources in real life, which possibly results in poor colors. In this study, we adopted a genetic algorithm and a large dataset of real light sources to identify an optimal set of sources that can better represent the sources in real life. The experiment results suggested that the identified set of sources can result in better color performance. Moreover, the selection of the sources was much less complicated in comparison to manual selections, which can be considered and implemented in practice.
UR - https://www.scopus.com/pages/publications/105000693079
U2 - 10.2352/CIC.2024.32.1.11
DO - 10.2352/CIC.2024.32.1.11
M3 - Conference article published in proceeding or book
AN - SCOPUS:105000693079
T3 - Final Program and Proceedings - IS and T/SID Color Imaging Conference
SP - 51
EP - 55
BT - Final Program and Proceedings - IS and T/SID Color Imaging Conference
PB - Society for Imaging Science and Technology
T2 - 32st Color and Imaging Conference - Color Science and Engineering Systems, Technologies, and Applications, CIC 2024
Y2 - 28 October 2024 through 1 November 2024
ER -