Translator Disclaimer
15 April 2008 Applications of super-resolution and deblurring to practical sensors
Author Affiliations +
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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
S. Susan Young, Richard Sims, Keith Kraples, James Waterman, Leslie Smith, Eddie Jacobs, Ted Corbin, Louis Larsen, and Ronald G. Driggers "Applications of super-resolution and deblurring to practical sensors", Proc. SPIE 6941, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XIX, 69411E (15 April 2008);

Back to Top