Human task performance on detecting distant targets under cluttered background in NIR and LWIR
This study investigates human ability to detect distant targets in cluttered backgrounds using NIR and LWIR, aiming to facilitate AI performance analysis. Through perception tests and employing NV-IPM, it reveals key insights into how image quality influences detectability across NIR and LWIR scenarios.
Authors
- Eddie L. Jacobs (ORCID: https://orcid.org/0000-0002-6304-8381)
- C. Kyle Renshaw (ORCID: https://orcid.org/0000-0001-8318-8333)
- Li Zhang (ORCID: https://orcid.org/0000-0002-0698-0754)
- lOrges Furshi
- Ronald G. Driggers
- Mark Martino (ORCID: https://orcid.org/0009-0004-8729-4773)
Institutions
- University of Central Florida (US)
- University of Arizona (US)
- University of Memphis (US)
Publication Details
- Published
- 2024-08-14
- DOI
- https://doi.org/10.1109/rapid60772.2024.10647032
- Primary Topic
- Infrared Target Detection Methodologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Army Research Laboratory