Chromatic aberration correction using reinforcement learning

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

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

OriginalspracheEnglisch
TitelEmerging Topics in Artificial Intelligence, ETAI 2023
Redakteure/-innenGiovanni Volpe, Joana B. Pereira, Daniel Brunner, Aydogan Ozcan
Herausgeber (Verlag)SPIE - The international society for optics and photonics
ISBN (elektronisch)9781510665248
PublikationsstatusVeröffentlicht - 2023
Peer-Review-StatusJa

Publikationsreihe

ReiheProceedings of SPIE - The International Society for Optical Engineering
Band12655
ISSN0277-786X

Konferenz

Titel2023 Emerging Topics in Artificial Intelligence
KurztitelETAI 2023
Dauer20 - 24 August 2023
OrtSan Diego Convention Center
StadtSan Diego
LandUSA/Vereinigte Staaten

Externe IDs

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

Schlagworte

Schlagwörter

  • aberration correction, chromatic aberrations, holography, reinforcement learning