Algorithm for radiometrically-accurate nonuniformity correction with arbitrary scene motion

This paper describes a major generalization of a recently reported radiometrically-accurate algebraic nonuniformity correction (NUC) algorithm. The original technique was capable of accurately estimating the bias nonuniformity from a sequence of pairs of images exhibiting strictly one-dimensional (ID) subpixel shifts. The new technique relaxes the subpixel 1D shift constraint to arbitrary two-dimensional (2D) motion, which can be either sub-pixel or super-pixel. The 2D technique relies on calibrating only rows and columns on the perimeter of the array, which in turn, provides the algorithm with the necessary initial conditions to recursively estimate the bias values in the entire array. In this way, radiometric NUC can be achieved non-disruptively, as needed, without disturbing the functionality of the interior array elements. The 2D algorithm is highly localized in time and space lending itself to near real-time implementation. Radiometric NUC can be achieved with a relatively low number of frames (typically about 10 frame pairs). Moreover, as in its earlier ID version, the performance of the 2D algorithm is shown to be insensitive to spatial diversity in the scene. This paper will address the performance of the 2D technique using real infrared data.