Video noise reduction in the wavelet domain using temporal decorrelation and adaptive thresholding
This paper proposes a novel wavelet domain based spatio-temporal filter for video denoising that exploits the temporal as well as spatial correlations which exist in the subband representation of the video sequence. The temporal redundancy or correlation among the corresponding wavelet coefficients in neighboring frames is minimized by the use of discrete cosine transform. These decorrelated noisy wavelet coefficients are then denoised spatially via a low-complexity wavelet shrinkage method, which utilizes the correlation that exists between subsequent resolution levels. The proposed scheme shows promising results and outperforms state-of-the-art spatio-temporal filters in time as well as wavelet domains, both in terms of PSNR and visual quality