Using post-processing filters to enhance image detail, a process commonly referred to as boost, can significantly affect the performance of an EO/IR system. The US Army's target acquisition models currently use the Targeting Task Performance (TTP) metric to quantify sensor performance. The TTP metric accounts for each element in the system including: blur and noise introduced by the imager, any additional post-processing steps, and the effects of the Human Visual System (HVS). The current implementation of the TTP metric assumes spatial separability, which can introduce significant errors when the TTP is applied to systems using non-separable filters. To accurately apply the TTP metric to systems incorporating boost, we have implement a two-dimensional (2D) version of the TTP metric. The accuracy of the 2D TTP metric was verified through a series of perception experiments involving various levels of boost. The 2D TTP metric has been incorporated into the Night Vision Integrated Performance Model (NV-IPM) allowing accurate system modeling of non-separable image filters.

Date Published: 18 May 2012
PDF: 9 pages
Proc. SPIE 8355, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIII, 83550Y (18 May 2012); doi: 10.1117/12.920998

Published in SPIE Proceedings Vol. 8355:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIII
Gerald C. Holst; Keith A. Krapels, Editor(s)