Structure-Oriented Spatio-Temporal Video Noise Estimation

Noise can highly impact the performance of video processing algorithms. This paper proposes a new real-time spatio-temporal method for estimating the noise variance in video signals. The proposed algorithm selects 3D regions or cubes in the video signal with high intensity uniformity. The noise variance is estimated from the selected set of spatially, temporally and spatio-temporally intensity-uniform cubes using local variances calculated along homogeneous plains. The proposed algorithm works well for sequences with high structure and motion activity and outperforms other methods with a worst-case estimation error of 2 dB. It works well for highly noisy and non-noisy sequences