Predicting exploitation success on compressed imagery through common image quality metrics: an initial look

Christopher D. McGuinness; Patrick C. Hytla; Kevin L. Priddy

doi:10.1117/12.2181940

20 May 2015 Predicting exploitation success on compressed imagery through common image quality metrics: an initial look

Christopher D. McGuinness, Patrick C. Hytla, Kevin L. Priddy

Proceedings Volume 9464, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VI; 94640T (2015) https://doi.org/10.1117/12.2181940
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

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.

Citation Download Citation

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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