IRSUM: Inter-frame registration based non-uniformity correction using spatio-temporal update mask

摘要

We propose a novel scene-based non-uniformity correction method to achieve better fixed-pattern noise reduction and eliminate ghosting artifacts. Our approach is based on robust parameter updates via inter-frame registration and spatio-temporally consistent correction coefficients. We utilized a GMM-based spatio-temporal update mask to selectively refine the estimations of correction coefficients. The results of our experiments on an extensive dataset consisting of both synthetically corrupted data and real infrared videos show that the proposed algorithm achieves superior performance in PSXR and roughness metrics with notably lower ghosting artifacts when compared to other state-of-the-art methods.