Spatio-temporal approach for noise estimation

We propose an efficient and accurate wavelet based :noise estimation method for white Gaussian noise in video sequences. The proposed method analyzes the distribution of spatial and temporal gradients in the video sequence in order to estimate the noise variance. The estimate is derived from the most frequent gradient in the two distributions and is compensated for the errors due to the spatio-temporal image sequence content, by a novel correction function. The main application of the proposed algorithm is for the estimation of the stationary Gaussian noise in wavelet based video processing, for which we show that the proposed method is more accurate than other state-of-the-art noise estimation techniques and less sensitive to varying spatio-temporal content and noise level. Furthermore, we adapt the algorithm for local noise estimation and test its performance.