Stand-off base and force protection surveillance measures primarily rely on electro-optic and thermal imaging technology. Atmospheric turbulence causes blur, distortion and intensity fluctuations that can severely degrade the image quality of these systems. This work explores the effects of turbulence image degradation on the performance of automatic facial recognition software and also looks at the potential benefit of turbulence mitigation algorithms. The goal of this work is to understand the feasibility of long-range facial recognition in degraded imaging conditions. In order to create a large enough database to match against, simulated imagery of different ranges and turbulence conditions were created using a horizontal view turbulence simulator and a subset of the Facial Recognition Technology (FERET) database. The simulated turbulence degraded imagery was then processed with facial recognition software and the results are compared against those from the pristine image set. Finally, the performance of the facial recognition software with turbulence mitigated imagery is also presented.
Active imaging systems, including laser range-gated short wave infrared (LRG SWIR) systems, are currently being
developed to increase the identification range performance of electro-optical targeting systems. This paper reports on the
development of an end-to-end simulation of a LRG SWIR imaging system that includes the principle phenomena of
beam broadening, beam jitter, scintillation, atmospheric turbulence blur and distortion, laser speckle and camera blur.
Although the simulation is restricted to weak turbulence conditions, it is much less computationally expensive than the
classical the split-step Fourier-transform algorithm.
KEYWORDS: Sensors, 3D modeling, Video, Detection and tracking algorithms, Video surveillance, Roads, Algorithm development, Data modeling, Visualization, Buildings
PerSEval is a modeling and simulation tool being developed for end-to-end evaluation of airborne persistent surveillance
imaging sensor systems. This class of sensor systems is characterized by having a wide coverage area over an extended
period of time and operating in either visible or thermal infrared wavebands. Current operational systems are heavily
used by image analysts for tracking vehicles or dismounted personnel, with an emphasis in urban areas of interest.
Future persistent surveillance systems will include automated ground target tracking algorithms to alleviate analyst
workload. As a system evaluation tool, PerSEval will include dependencies on the scenario, platform, sensor, processing,
and tracking algorithm. This paper describes the overall PerSEval architecture as well as the first phase of development
which focuses on the creation of a three-dimensional urban terrain simulation appropriate for the evaluation of
automated tracking algorithms.
Active imaging systems, including laser range-gated short wave infrared (LRG SWIR) systems, are currently being
developed to increase the identification range performance of ground-to-ground electro-optical targeting systems. These
systems have several distinct technological and practical advantages over passive systems, but they also suffer from
peculiar phenomena, including laser speckle. This paper reports on a study in which the benefits of speckle reduction
techniques on the ability of observers to identify human activities were determined empirically. Since no suitable LRG
SWIR imagery existed, it was necessary to first develop a simulation of speckle formation in a typical LRG SWIR
imager, which also included the chosen speckle reduction techniques. The simulation was then applied to a human
activities target set and the resulting imagery evaluated in a perception experiment.
The signature of any vehicle does not exist as an entity in its own right, but depends on the environment, the interaction between the environment and the vehicle, and the background against which it is detected by a sensor. CAMEO-SIM was initially developed as a broad-band (0.4 - 14 micron) scene generation system for the assessment of air vehicle camouflage effectiveness, but it can be used to simulate any kind of object and its interactions with the environment. The thermal, spectral, spatial and directional effects of sources, surfaces and the atmosphere are modeled in a fully three-dimensional environment. CAMEO-SIM was designed to be a scaleable system that can produce images to different levels of fidelity. Rendering time can be balanced against the fidelity required so that the images produced are 'fit for purpose;' in its lowest fidelity operation it can create real-time in-band imagery but when operated at its highest fidelity the subtle, complex spectral and spatial effects that arise in the real- world are more closely captured. This paper describes the current system, details the verification tests that have been undertaken, and discusses the significance of particular effects such as shadows, and directional reflectance, on the accuracy of the final image.
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