Simultaneous MAP-based video denoising and rate-distortion optimized video encoding
IEEE Transactions on Circuits and Systems for Video Technology
Patch-based video processing: a variational Bayesian approach
IEEE Transactions on Circuits and Systems for Video Technology
Image and video denoising using adaptive dual-tree discrete wavelet packets
IEEE Transactions on Circuits and Systems for Video Technology
A fuzzy filter for the removal of random impulse noise in image sequences
Image and Vision Computing
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Denoising module is required by any practical video processing systems. Most existing denoising schemes are spatio-temporal filters which operate on data over three dimensions. However, to limit the number of inputs, these filters only utilize one reference frame and cannot fully exploit temporal correlation. In this paper, a recursive temporal denoising filter named multihypothesis motion compensated filter (MHMCF) is proposed. To fully exploit temporal correlation, MHMCF performs motion estimation in a number of reference frames to construct multiple hypotheses (temporal predictions) of the current pixel. These hypotheses are combined by weighted averaging to suppress noise and estimate the actual current pixel value. Based on the multihypothesis motion compensated residue model presented in this paper, we investigate the efficiency of MHMCF, and some numerical evaluations are revealed. Experimental results show that MHMCF demonstrates quite good denoising performance while the inputs are much fewer than spatio-temporal filters. Moreover, as a purely temporal filter, it can well preserve spatial details and achieve satisfactory visual quality.