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.
It is often difficult to determine the precise characteristics that a hyperspectral sensor must have to meet mission objectives, but this information is crucial for designing a successful mission. We have developed a tool which emulates data from hyperspectral sensors by degrading other hyperspectral imagery. The tool performs target detection on the emulated imagery and assesses the utility of the modelled sensor based on detection performance. We will present details of how the tool functions; validation of the tool against airborne hyperspectral data; and extrapolations showing the estimated performance of different sensor configurations outside the validation envelope.
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.
Novel types of spectral sensors using coded apertures may offer various advantages over conventional designs, especially the possibility of compressive measurements that could exceed the expected spatial, temporal or spectral resolution of the system. However, the nature of the measurement process imposes certain limitations, especially on the noise performance of the sensor. This paper considers a particular type of coded-aperture spectral imager and uses analytical and numerical modelling to compare its expected noise performance with conventional hyperspectral sensors. It is shown that conventional sensors may have an advantage in conditions where signal levels are high, such as bright light or slow scanning, but that coded-aperture sensors may be advantageous in low-signal conditions.
Emotional or physical stresses induce a surge of adrenaline in the blood stream under the command of the sympathetic
nerve system, which, cannot be suppressed by training. The onset of this alleviated level of adrenaline triggers a number
of physiological chain reactions in the body, such as dilation of pupil and an increased feed of blood to muscles etc. This
paper reports for the first time how Electro-Optics (EO) technologies such as hyperspectral [1,2] and thermal imaging[3]
methods can be used for the detection of stress remotely. Preliminary result using hyperspectral imaging technique has
shown a positive identification of stress through an elevation of haemoglobin oxygenation saturation level in the facial
region, and the effect is seen more prominently for the physical stressor than the emotional one. However, all results
presented so far in this work have been interpreted together with the base line information as the reference point, and that
really has limited the overall usefulness of the developing technology. The present result has highlighted this drawback
and it prompts for the need of a quantitative assessment of the oxygenation saturation and to correlate it directly with the
stress level as the top priority of the next stage of research.
This paper reports how Electro-Optics (EO) technologies such as thermal and hyperspectral [1-3] imaging methods can
be used for the detection of stress remotely. Emotional or physical stresses induce a surge of adrenaline in the blood
stream under the command of the sympathetic nerve system, which, cannot be suppressed by training. The onset of this
alleviated level of adrenaline triggers a number of physiological chain reactions in the body, such as dilation of pupil and
an increased feed of blood to muscles etc. The capture of physiological responses, specifically the increase of blood
volume to pupil, have been reported by Pavlidis's pioneer thermal imaging work [4-7] who has shown a remarkable
increase of skin temperature in the periorbital region at the onset of stress. Our data has shown that other areas such as
the forehead, neck and cheek also exhibit alleviated skin temperatures dependent on the types of stressors. Our result has
also observed very similar thermal patterns due to physical exercising, to the one that induced by other physical stressors,
apparently in contradiction to Pavlidis's work [8]. Furthermore, we have found patches of alleviated temperature regions
in the forehead forming patterns characteristic to the types of stressors, dependent on whether they are physical or
emotional in origin. These stress induced thermal patterns have been seen to be quite distinct to the one resulting from
having high fever.
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