Visual sensing capabilities are critical in surveillance and rescue operations. Detection, Recognition, and Identification performance are used to measure the ability to distinguish specific objects. In traditional vision camera-based surveillance systems, the image quality is directly affected by the atmosphere and weather. Smoke, haze, fog, and humidity reduce the contrast and signal to noise ratio of an image. The DRI performance is affected by visual capabilities, so there is an urgent need to improve the image quality in extreme environmental conditions. To penetrate haze conditions, proper wavelength selection and hyperspectral imaging help minimize scattering effects from atmosphere and improve the ability of object identification. In traditional hyperspectral imaging systems, a line-scan technique is dominant as it is major for material or quality inspection. For surveillance system, it is not appropriate as it will suffer from lower temporal resolution and cause image distortion. In this project, a shortwave infrared band camera optical system with tunable filter based spectral imaging system will be developed. The system is targeted for surveillance applications, especially for long distance sensing in extreme environmental conditions. Benefit from tunable filter design, it fulfills the high temporal, spatial and spectral data requirement for visual analysis purposes. The higher contrast and SNR data enables the object identification capabilities under extreme environmental conditions, it particular useful in long-distance sensing, coastal surveillance and rescue applications.
