Many applications generate digital image sequences using a lens system, a light-transducing pixel array, and
sample-and-hold A/D electronics. Non-uniformity Correction (NUC) is an image processing operation that is
often required in such systems. The NUC operation subtracts the background from a temporally evolving image
on a pixel-by-pixel basis. Background estimation must be robust against image features, electronic glitches, and
sudden changes in background. The NUC is often applied in conjunction with a mechanical image dithering that
enables separation of the image from the static additive background. In real-time applications with large pixe-count
focal planes, the NUC must process large data bandwidths. The NUC algorithm must be operationally
efficient to process data in real time. This paper examines a number of NUC algorithms. It defines a set of
performance metrics and evaluates algorithm performance in terms of trades between these metrics and processing
cost. It provides a guide for selecting an appropriate NUC algorithm based on operating conditions and available
compute resources.
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