Efficient numerical method for flat-field correction in complex optical systems with minimal data collection

Lucy Ying-Ju Chu; Jiang He; Sean Huentelman; Huayan Luo; Siyuan Liang; Lucas Wang; Kevin Fan; Wei Zhou

doi:10.1117/12.3028846

30 September 2024 Efficient numerical method for flat-field correction in complex optical systems with minimal data collection

Lucy Ying-Ju Chu, Jiang He, Sean Huentelman, Huayan Luo, Siyuan Liang, Lucas Wang, Kevin Fan, Wei Zhou

Author Affiliations +

Proceedings Volume 13133, Optical System Alignment, Tolerancing, and Verification XV; 1313308 (2024) https://doi.org/10.1117/12.3028846
Event: Optical Engineering + Applications, 2024, San Diego, California, United States

Abstract

Flat-field correction (FFC) is essential for addressing relative illuminance roll-off in optical imaging systems, a calibration process that requires capturing an image of a uniform light source. In imaging systems capable of mimicking or measuring SPH, CYL, AXIS, such as those used for eye prescriptions, the number of images required to collect for FFC increases with each lens adjustment. We propose a numerical method that uses a few core images to synthesize FFC images for various configurations, reducing data requirements substantially. This method was validated on two imaging systems with differing optical alignment quality, achieving relative illuminance falloff of less than 2% with only 5% the amount of the original data.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lucy Ying-Ju Chu, Jiang He, Sean Huentelman, Huayan Luo, Siyuan Liang, Lucas Wang, Kevin Fan, and Wei Zhou "Efficient numerical method for flat-field correction in complex optical systems with minimal data collection", Proc. SPIE 13133, Optical System Alignment, Tolerancing, and Verification XV, 1313308 (30 September 2024); https://doi.org/10.1117/12.3028846

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