This paper describes a comprehensive computational imaging field trial conducted in Meppen, Germany, aimed at assessing the performance of cutting-edge computational imaging systems (compressive hyper-spectral, visible/shortwave infrared single-pixel, wide-area infrared, neuromorphic, high-speed, photon counting cameras, and many more) by the members of NATO SET-RTG-310. The trial encompassed a diverse set of targets, including dismounts equipped with various two-handheld objects and adorned with a range of camouflage patterns, as well as fixed and rotary-wing Unmanned Aerial System (UAS) targets. These targets covered the entire spectrum of spatial, temporal, and spectral signatures, forming a comprehensive trade space for performance evaluation of each system. The trial, which serves as the foundation for subsequent data analysis, encompassed a multitude of scenarios designed to challenge the limits of computational imaging technologies. The diverse set of targets, each with its unique set of challenges, allows for the examination of system performance across various environmental and operational conditions.
This paper describes a comprehensive computational imaging field trial conducted in Meppen, Germany, aimed at assessing the performance of cutting-edge computational imaging systems (compressive hyperspectral, visible/shortwave infrared single-pixel, wide-area infrared, neuromorphic, high-speed, photon counting cameras, and many more) by the members of NATO SET-RTG-310. The trial encompassed a diverse set of targets, including dismounts equipped with various two-handheld objects and adorned with a range of camouflage patterns, as well as fixed and rotary-wing Unmanned Aerial System (UAS) targets. These targets covered the entire spectrum of spatial, temporal, and spectral signatures, forming a comprehensive trade space for performance evaluation of each system.
The trial, which serves as the foundation for subsequent data analysis, encompassed a multitude of scenarios designed to challenge the limits of computational imaging technologies. The diverse set of targets, each with its unique set of challenges, allows for the examination of system performance across various environmental and operational conditions.
Conventional electro-optical and infrared (EO/IR) systems (i.e., active, passive, multiband and hyperspectral) capture an image by optically focusing the incident light at each of the millions of pixels in a focal plane array. The optics and the focal plane are designed to efficiently capture desired aspects (like spectral content, spatial resolution, depth of focus, polarization, etc.) of the scene. Computational imaging refers to image formation techniques that use digital computation to recover an image from an appropriately multiplexed or coded light intensity of the scene. In this case, the desired aspects of the scene can be selected at the time of image reconstruction which allows greater flexibility of the EO/IR system. Compressive sensing involves capturing a smaller number of specifically designed measurements from the scene to computationally recover the image or task specific scene information. Compressive sensing has the potential to acquire an image with equivalent information content to a large format array while using smaller, cheaper, and lower bandwidth components. More significantly, the data acquisition can be sequenced and designed to capture task specific and mission relevant information guided by the scene content with more flexibility. However, the benefits of compressive sensing and computational imaging do not come without compromise. NATO SET-232 has undertaken the task of investigating the promise of computational imaging and compressive sensing for EO/IR systems. This paper presents an overview of the ongoing joint activities by NATO SET-232, current computational imaging and compressive sensing technologies, limitations of the design trade space, algorithm and conceptual design considerations, and field performance assessment and modeling.
The Georgia Tech Research Institute is currently developing a device to demonstrate a hands-free focus technology for
head-mounted night vision sensors. The demonstrator device will integrate a computational imaging technique that
increases depth of field with a digital night vision sensor. The goal of the demonstrator is to serve as a test bed for
evaluating the critical performance/operational parameters necessary for the hands-free focus technology to support
future tactical night vision concepts of operation. This paper will provide an overview of the technology studies and
design analyses that have been performed to date as well as the current state of the demonstrator design.
Although existing night vision equipment provides a significant improvement in target detection in low light conditions,
there are several limitations that limit their effectiveness. Focus is a significant problem for night vision equipment due
to the low f-number optics required to obtain sufficient sensitivity as well as the dynamic nature of night vision
applications, which requires frequent focus adjustments. The Georgia Tech Research Institute has developed a prototype
next-generation night vision device called the Improved Night Vision Demonstrator (INVD) in order to address these
shortfalls. This paper will describe the design of the INVD system as well as an analysis of its performance.
Although the potential benefits of infrared imaging systems in law enforcement applications have been apparent for many years, budget and technology constraints have prevented their widespread deployment. Recent technology improvements and cost reductions, however, have made the routine use of handheld thermal imagers practical for the law enforcement community. This effort involved both an analysis of operational and technical requirements associated with law enforcement use as well as a comprehensive review of commercially available handheld infrared imaging systems. The use of handheld infrared systems in the counterdrug environment is also addressed, including the results of an analysis of proven applications, a review of training requirements, and a summary of legal issues associated with infrared surveillance. Results generated by the NVTHERM infrared sensor model are also shown for one handheld imager to provide representative information regarding low-cost thermal imager performance.
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