Video Signal-Dependent Noise Estimation via Inter-Frame Prediction

We propose a block-based signal-dependent noise estimation method on videos, that leverages inter-frame redundancy to separate noise from signal. Block matching is applied to find block pairs between two consecutive frames with similar signal. Then Ponomarenko’s method is extended by sorting pairs by their low-frequency energy and estimating noise in the high frequencies. Experiments on three datasets show that this method improves on the state of the art.