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20 May 2015 Predicting exploitation success on compressed imagery through common image quality metrics: an initial look
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Abstract
Imagery from unmanned aerial systems (UAS) needs compression prior to transmission to a receiver for further processing. Once received, automated image exploitation algorithms, such as frame-to-frame registration, target tracking, and target identification, are performed to extract actionable information from the data. Unfortunately, in a compress-then-analyze system, exploitation algorithms must contend with artifacts introduced by lossy compression and transmission. Identifying metrics that enable compression engines to predict exploitation degradation could allow encoders the ability of tailoring compression for specific exploitation algorithms. This study investigates the impact of H.264 and JPEG2000 compression on target tracking through the use of a multi-hypothesis blob tracker. Used quality metrics include PSNR, VIF, and IW-SSIM.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christopher D. McGuinness, Patrick C. Hytla, and Kevin L. Priddy "Predicting exploitation success on compressed imagery through common image quality metrics: an initial look", Proc. SPIE 9464, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VI, 94640T (20 May 2015); https://doi.org/10.1117/12.2181940
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