Open AccessValidation of modeled sparse aperture post-processing artifacts
Author(s) -
Philip S. Salvaggio,
John R. Schott,
Donald M. McKeown
Publication year - 2017
Publication title -
applied optics
Language(s) - Uncategorized
Resource type - Journals
ISSN - 0003-6935
DOI - 10.1364/ao.56.000761
Subject(s) - computer science , image processing , image quality , artificial intelligence , computer vision , signal processing , synthetic aperture radar , noise (video) , aperture (computer memory) , optics , image (mathematics) , telecommunications , physics , radar , acoustics
Sparse aperture imaging introduces a number of interesting image quality issues. Just as with traditional systems, resolution, signal-to-noise ratio, and post processing are all relevant to image quality. This work will examine post-processing artifacts that arise in sparse aperture imagery, which are more complex than the edge-overshoot artifacts that appear in traditional imagery. Modeling has predicted the existence of these artifacts. This work will verify that prediction with real data. Artifacts rising from various causes will be examined. It will be established that model predictions can be used in future trade studies regarding artifacting.