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Proceedings Paper

Comparative analysis of infrared images degraded by lossy compression techniques
Author(s): W. Alex Toussaint; Reed A. Weber
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Paper Abstract

This work addresses image degradation introduced by lossy compression techniques and the effects of such degradation on signal detection statistics for applications in fast-framing (<100 Hz) IR image analysis. As future space systems make use of increasingly higher pixel count IR focal plane arrays, data generation rates are anticipated to become too copious for continuous download. The prevailing solution to this issue has been to compress image data prior to downlink. While this solution is application independent for lossless compression, the expected benefits of lossy compression, including higher compression ratio, necessitate several application specific trades in order to characterize preservation of critical information within the data. Current analyses via standard statistical image processing techniques following tunably lossy compression algorithms (JPEG2000, JPEG-LS) allow for detection statistics nearly identical to analyses following standard lossless compression techniques, such as Rice and PNG, even at degradation levels offering a greater than twofold increase in compression ratio. Ongoing efforts focus on repeating the analysis for other tunably lossy compression techniques while also assessing the relative computational burden of each algorithm. Current results suggest that lossy compression techniques can preserve critical information in fast-framing IR data while either significantly reducing downlink bandwidth requirements or significantly increasing the usable focal plane array window size.

Paper Details

Date Published: 1 September 2015
PDF: 8 pages
Proc. SPIE 9608, Infrared Remote Sensing and Instrumentation XXIII, 96080L (1 September 2015); doi: 10.1117/12.2188487
Show Author Affiliations
W. Alex Toussaint, Boston College (United States)
Reed A. Weber, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 9608:
Infrared Remote Sensing and Instrumentation XXIII
Marija Strojnik Scholl; Gonzalo Páez, Editor(s)

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