Space low-pass and temporal high-pass nonuniformity correction algorithm

Abstract

Nowadays, almost all scene-based nonuniformity correction (NUC) algorithms have the same shortcoming: a low convergence speed. This shortcoming produces ghosting artifacts. In this paper, we will start by discussing the traditional temporal high-pass NUC algorithm, and then combine the space frequency and temporal frequency. This combination will produce a new algorithm called the space low-pass and temporal high-pass NUC algorithm. The kernel idea of this algorithm is to eliminate the nonuniformity’s high-space-frequency part and retain the nonuniformity’s low-space-frequency part. Moreover, the high-space-frequency part’s processing is controllable, which markedly increases convergence speed. These features make our algorithm’s convergence speed so high that processed images have almost no ghosting artifacts.