Improving closely spaced dim object detection through multiframe blind deconvolution of near stellar neighbourhoods

Authors

Stephen C. Cain, Air Force Institute of TechnologyFollow
Ronald M. Aung, Air Force Institute of Technology

Document Type

Article

Publication Date

9-2-2020

Abstract

Excerpt: A new iterative algorithm is proposed to improve the detection of dim stellar objects that are in the neighbourhood of a bright object, using short-exposure images. This method separates data functions into the primary bright object function, the neighbourhood system function, and the background function. Abstract © Taylor & Francis.

Comments

This article is available via subscription or purchase through the DOI link below.

Co-author Ronald Aung was completing his AFIT PhD program at the time of this article. (AFIT-ENG-DS-20-S-004, September 2020)

Funding note: This work was supported by Air Force Office of Scientific Research [grant number F4FGA09014J00318].

DOI

10.1080/09500340.2020.1810345

Source Publication

Journal of Modern Optics (ISSN 0950-0340)

Recommended Citation

Aung, R. M., & Cain, S. C. (2020). Improving closely spaced dim object detection through multiframe blind deconvolution of near stellar neighbourhoods. Journal of Modern Optics, 67(13), 1145–1158. https://doi.org/10.1080/09500340.2020.1810345