A METHOD FOR CONFIDENT REGISTRATION-BASED NON-UNIFORMITY CORRECTION USING SPATIO-TEMPORAL UPDATE MASK

摘要

A scene-based non-uniformity correction method to achieve a fixed-pattern noise reduction and eliminate ghosting artifacts based on robust parameter updates via a confident inter-frame registration and spatio-temporally consistent correction coefficients. The method includes the steps of: Assessing an input image frame whether the input image frame has a sufficient scene detail for registrations to prevent false registrations originated from low-detail scenes, calculating horizontal and vertical translations between frames to find a shift, introducing a scene-adaptive registration quality metric to eliminate erroneous parameter updates resulting from unreliable registrations and applying a Gaussian mixture model (GMM)-based temporal consistency restriction to mask out unstable updates in non-uniformity correction parameters.