In image formation and recording process, there are many factors that affect sensor performance and image quality that result in loss of high-frequency information. Two of these common factors are undersampled sensors and sensor's blurring function. Two image processing algorithms, including super-resolution image reconstruction and deblur filtering, have been developed based on characterizing the sources of image degradation from image formation and recording process. In this paper, we discuss the applications of these two algorithms to three practical thermal imaging systems. First, super-resolution and deblurring are applied to a longwave uncooled sensor in a missile seeker. Target resolution is improved in the flight phase of the seeker operation. Second, these two algorithms are applied to a midwave target acquisition sensor for use in long-range target identification. Third, the two algorithms are applied to a naval midwave distributed aperture sensor (DAS) for infrared search and track (IRST) system that is dual use in missile detection and force protection/anti-terrorism applications. In this case, super-resolution and deblurring are used to improve the resolution of on-deck activity discrimination.

Date Published: 15 April 2008
PDF: 11 pages
Proc. SPIE 6941, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XIX, 69411E (15 April 2008); doi: 10.1117/12.796420

Published in SPIE Proceedings Vol. 6941:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XIX
Gerald C. Holst, Editor(s)