Increasing the depth of field in an LWIR system for improved object identification

Abstract

In a long wave infrared (LWIR) system there is the need to capture the maximum amount of information of objects over a broad volume for the identification and classification by the human or machine observer. In a traditional imaging system the optics limit the capture of this information to a narrow object volume. This limitation can hinder the observer's ability to navigate and/or identify friend or foe in combat or civilian operations. By giving the observer a larger volume of clear imagery their ability to perform will drastically improve. The system presented allows the efficient capture of object information over a broad volume and is enabled by a technology called Wavefront Coding. A Wavefront Coded system employs the joint optimization of the optics, detection and signal processing. Through a specialized design of the system’s optical phase, the system becomes invariant to the aberrations that traditionally limit the effective volume of clear imagery. In the process of becoming invariant, the specialized phase creates a uniform blur across the detected image. Signal processing is applied to remove the blur, resulting in a high quality image. A device specific noise model is presented that was developed for the optimization and accurate simulation of the system. Additionally, still images taken from a video feed from the as-built system are shown, allowing the side by side comparison of a Wavefront Coded and traditional imaging system.