Robust nonuniformity correction in infrared images based on global motion

The presence of spatial and temporal fixed pattern noise (FPN) due to nonuniformity in sensor parameters is a well known problem in IR focal plane detector arrays. In order to obtain a noise-free image, the nonuniformity parameters should be estimated and compensated for. This work presents a scene-based nonuniformity correction (NUC) algorithm that estimates and compensates the nonuniformity parameters by equalizing output of different detectors that were exposed to the same information. The correspondence between pixels is found via an improved robust global motion estimation technique that locates and excludes local motion and occlusion regions from the estimation of motion parameters. The performance of the proposed algorithm is evaluated both in image sequences with simulated fixed-pattern noise and real infrared image sequences. Significant reduction in FPN is demonstrated in both cases.