| Improved imaging and detection of objects through turbid obscurants is a vital problem of current interest to both military and civilian entities. Image quality is severely degraded when obscurant fields such as fog, smoke, dust, etc., lie between an object and the light-collecting optics. Conventional intensity imaging through turbid media suffers from rapid loss of image contrast due to light scattering from particles (e.g. in fog) or random variations of refractive index (e.g. in medical imaging). Intensity imaging does not differentiate between rays scattered off particles in the obscurant field and those reflected off objects within the field. Scattering degrades image quality in all spectral bands (UV, visible, and IR), although the amount of degradation is wavelength dependent. This dissertation features the development of innovative system designs and techniques that utilize scattered radiation’s deterministic polarization state evolution to greatly enhance the image contrast of stand-off objects within obscurant fields such as smoke, fog, or dust using active polarized illumination in the visible. The produced sensors acquire and process image data in real time using computationally non-intensive algorithms that differentiate between radiation that scatters or reflects from obscured objects and the radiation from the scattering media, improving image contrast by factors of ten or greater for dense water vapor obscurants. |
