In multispectral imaging systems, correction for lens distortion is required to allow pixel by pixel fusion techniques to be applied. In producing a multispectral imaging system in significant quantities, the process of generating the corrections needs to be largely automated as each lens will require its own corrections. This thesis presents an auto-correction and bench sighting method applicable to a dual band, helmet mounted, night vision goggle. In principle, the method is to determine the

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... istortion parameters of production optics by imaging a calibration target, and then use the distortion parameters to correct the distortion. The goal of this work is to calibrate the imagery from the long wave infrared (LWIR) sensor within this night vision system. First, an overview of lens distortion models, correction methods, and calibration targets are presented. Next, the unique constraints that frame the problem, real-time processing with limited computing resources, and image scale space constraints, are discussed. Given the constraints, the working solution is presented. The solution is multi-fold; it consists of an LWIR-band calibration target, a suite of algorithms to characterize the lens distortion, and a correction "warp" map. This approach incorporates a new scale-preserving distortion model, and a novel error metric. Each step of the correction process is discussed in detail, with intermediate results presented. Visual results are shown of both corrected and un-corrected imagery. Finally, the robustness of the algorithm is discussed. ii