No abstract

A new direction for the US Army Night Vision and Electronic Sensors Directorate is the development of ultra-narrow field of view (UNFOV) infrared target acquisition (TA) systems. Frequently, the performance of these systems is limited by atmospheric turbulence in the imaging path. It is desirable to include the effects of atmospheric turbulence blur in infrared TA models. The current TA models are currently linear shift invariant (LSI) systems with component modulation transfer functions (MTFs). The use of additional MTFs, to account for atmospheric turbulence, requires that the turbulence blur have LSI properties. The primary unresolved issue with the treatment of turbulence blur as an MTF is the LSI characteristics of the blur. Significant variation in spatial blur and temporal blur prohibit the use of a single MTF in an LSI target acquisition model. Researchers at Ben-Gurion University (BGU) use a TA model that includes an LSI blur, which is a temporal average of the turbulence blur. The research described here evaluates the BGU-type treatment of atmospheric MTF and determines it reasonable for inclusion in the US Army's TA model. In addition to the spatial characteristics, the temporal variation of the turbulence blur is also described.

Current target acquisition models are for monochrome imagery systems (single detector). The increasing interest in multispectral infrared systems and color daylight imagers highlights the need for models that describe the target acquisition process for color systems (2 or more detectors).This study investigates the detection of simple color targets in a noisy color background. Color targets are varied separately either in hue or saturation. Noise is created with a mixture ofrandom hue and saturation combinations. Our preliminary result showed a simple two-color (yellow-blue) representation did not improve the standard black-and-white Minimum Resolvable Temperature Difference sensitivity. Subsequent psychophysical experiments reveal that human hue and saturation discriminations interact (the Abney effect) and need to be separated in color target detection modeling. Research is continuing to better define the mathematical relationship between the target acquisition parameters (e.g., temperature difference or intensity contrast) and the color space of hue and saturation.