Chromatic aberration correction using reinforcement learning

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Abstract

Chromatic aberrations can significantly diminish image quality when employing multiple wavelengths for imaging with a single optical system due to dispersion in both optical system and samples. To tackle this problem, we propose a novel approach using an adaptive achromatic lens, which is controlled by a trained Reinforcement Learning agent as part of a machine learning method. Notably, our method corrects chromatic aberrations prior to the imaging process, distinguishing it from conventional software-based post-processing approaches.

Details

Original languageEnglish
Title of host publicationEmerging Topics in Artificial Intelligence, ETAI 2023
EditorsGiovanni Volpe, Joana B. Pereira, Daniel Brunner, Aydogan Ozcan
PublisherSPIE - The international society for optics and photonics
ISBN (electronic)9781510665248
Publication statusPublished - 2023
Peer-reviewedYes

Publication series

SeriesProceedings of SPIE - The International Society for Optical Engineering
Volume12655
ISSN0277-786X

Conference

Title2023 Emerging Topics in Artificial Intelligence
Abbreviated titleETAI 2023
Duration20 - 24 August 2023
LocationSan Diego Convention Center
CitySan Diego
CountryUnited States of America

External IDs

ORCID /0000-0003-4562-0759/work/190133628

Keywords

Keywords

  • aberration correction, chromatic aberrations, holography, reinforcement learning