Perceptual feedback in multigrid motion estimation using an improved DCT quantization

In this paper, a multigrid motion compensation video coder based on the current human visual system (HVS) contrast discrimination models is proposed. A novel procedure for the encoding of the prediction errors has been used. This procedure restricts the maximum perceptual distortion in each transform coefficient. This subjective redundancy removal procedure includes the amplitude nonlinearities and some temporal features of human perception. A perceptually weighted control of the adaptive motion estimation algorithm has also been derived from this model. Perceptual feedback in motion estimation ensures a perceptual balance between the motion estimation effort and the redundancy removal process. The results show that this feedback induces a scale-dependent refinement strategy that gives rise to more robust and meaningful motion estimation, which may facilitate higher level sequence interpretation. Perceptually meaningful distortion measures and the reconstructed frames show the subjective improvements of the proposed scheme versus an H.263 scheme with unweighted motion estimation and MPEG-like quantization.

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