A NON-LOCAL MEAN TEMPORAL FILTER FOR VIDEO COMPRESSION

Modern video codecs exploit the temporal and spatial correlations of video signal to achieve compression. The noise in video signal corrupts such correlations and impairs the coding efficiency. Prior works in VP8, VP9, and HEVC exploit the use of temporal filtering to remove certain noise from the source signal. They typically compare a pair of pixels along a motion trajectory and decide the filter coefficients based on the pixel value difference. It is observed that such noise removal allows better rate-distortion performance trade off and hence improves the objective compression efficiency. Note that the compression distortion is evaluated against the original video signal in all cases. This work proposes a non-local mean temporal filter for noise removal. Instead of comparing a pair of pixels along the motion trajectory, it compares two pixel blocks surrounding the pixels of interest. Their distance in L2 norm is then normalized by the frame noise level, which is used to determine the temporal filter coefficients in a non-parametric model. It is experimentally shown that the proposed non-local mean filter approach achieves improved compression efficiency over other contenders.