Computer vision applications for coronagraphic optical alignment and image processing

Abstract

Modern coronagraphic systems require very precise alignment between optical components and can benefit greatly from automated image processing. We discuss three techniques commonly employed in the fields of computer vision and image analysis as applied to the Gemini Planet Imager, a new facility instrument for the Gemini South Observatory. We describe how feature extraction and clustering methods can be used to aid in automated system alignment tasks, and also present a search algorithm for finding regular features in science images used for calibration and data processing. Along with discussions of each technique, we present our specific implementation and show results of each one in operation.

24 pages, 8 grayscale figures

References in corpus (4)

• Direct Imaging of Multiple Planets Orbiting the Star HR 8799
• Apodized Pupil Lyot Coronagraphs for Arbitrary Telescope Apertures
• Astrometry and Photometry with Coronagraphs
• Accurate Astrometry and Photometry of Saturated and Coronagraphic Point Spread Functions

Cited by in corpus (8)

• Reconnaissance of the HR 8799 Exosolar System II: Astrometry and Orbital Motion
• Gemini Planet Imager Observational Calibrations VIII: Characterization and Role of Satellite Spots
• Calibration of the island effect: Experimental validation of closed-loop focal plane wavefront control on Subaru/SCExAO
• Automated data processing architecture for the Gemini Planet Imager Exoplanet Survey
• Automated alignment of a reconfigurable optical system using focal-plane sensing and Kalman filtering
• On-sky performance during verification and commissioning of the Gemini Planet Imager's adaptive optics system
• Gemini Planet Imager One Button Approach
• Automated Alignment and On-Sky Performance of the Gemini Planet Imager Coronagraph