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Updated: May 11, 2026

Binocular Dynamic Visual Acuity in Eyeglass-Corrected Myopic Patients

Binocular Dynamic Visual Acuity in Eyeglass-Corrected Myopic Patients

Published on: March 29, 2022

Computer vision applications for coronagraphic optical alignment and image processing.

Dmitry Savransky¹, Sandrine J Thomas, Lisa A Poyneer

¹Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, California 94550, USA. savransky1@llnl.gov

|May 15, 2013

Summary

This summary is machine-generated.

Automated image processing using computer vision techniques aids coronagraphic systems. Feature extraction and clustering methods improve alignment and calibration for instruments like the Gemini Planet Imager.

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Area of Science:

Astronomy and Astrophysics
Computer Vision
Image Analysis

Background:

Coronagraphic systems demand high precision optical alignment.
Automated image processing offers significant benefits for these systems.

Purpose of the Study:

To apply computer vision and image analysis techniques to coronagraphic systems.
To demonstrate automated alignment and calibration using feature extraction, clustering, and search algorithms.

Main Methods:

Feature extraction and clustering for automated system alignment.
Development of a search algorithm for identifying regular features in science images.
Implementation and testing on the Gemini Planet Imager instrument.

Main Results:

Successful application of feature extraction and clustering for alignment tasks.
Demonstrated efficacy of the search algorithm in calibration and data processing.
Validation of techniques through operational results on the Gemini Planet Imager.

Conclusions:

Computer vision and image analysis techniques are effective for automating coronagraphic system alignment and calibration.
These methods enhance precision and efficiency in astronomical instrumentation.
The implemented algorithms provide practical solutions for operational challenges in observatories.