Patch-based video processing: a variational Bayesian approach
IEEE Transactions on Circuits and Systems for Video Technology
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Spatio-temporal adaptive 3-D Kalman filter for video
IEEE Transactions on Image Processing
Adaptive wavelet thresholding for image denoising and compression
IEEE Transactions on Image Processing
Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering
IEEE Transactions on Image Processing
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A novel method for reducing video noise by using wavelet shrinkage in the temporal-spatial domain was devised and evaluated. In a temporal-spatial wavelet transform, static areas in a picture appear in a temporal low-frequency sub-band. In regards to this sub-band, the wavelet shrinkage can use a high threshold value in a shrinkage function and attains good noise-reduction performance. On the other hand, moving areas in a picture appear at the temporal high-frequency sub-band in a wavelet transform. In this sub-band, the wavelet shrinkage can not use a high threshold value, so a combined algorithm with a spatial-median filter is used. The noise-reduction performance of the proposed method was confirmed by a subjective evaluation, which showed that the quality of the noise-reduced images produced by the devised method is superior to that produced by traditional noise-reduction methods.