Performance benefits of small-pitch, high-dynamic-range, digitally restored infrared imaging systems using triangle orientation discrimination and NVIPM

For the past year, the authors have been studying a long-wave infrared (LWIR) sensor design concept that combines high detector well capacity, small-pitch detectors, and digital image processing to optimize target acquisition. Theoretical performance modeling [via the Night Vision Integrated Performance Model (NVIPM)] suggests that our approach offers a large increase in target identification range, but multiple field trials using triangle orientation discrimination (TOD) have yielded results that are inconsistent with the model’s predictions. For this reason, we have performed human perception experiments on simulated TOD targets, with and without image processing, to assess the utility of our approach and the value of TOD as an evaluation for digital image enhancement. The results do not agree with the NVIPM modeling of range improvement. We present our results, along with our modeling and experiment methodologies, to guide future investigations into the effects of boost or restoration filtering on target identification performance.