Malo J, Gutierrez J, Epifanio I, Ferri F J, Artigas J M
Dept. d'Opt., Valencia Univ.
IEEE Trans Image Process. 2001;10(10):1411-27. doi: 10.1109/83.951528.
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.
本文提出了一种基于当前人类视觉系统(HVS)对比度辨别模型的多网格运动补偿视频编码器。采用了一种新颖的预测误差编码方法。该方法限制了每个变换系数中的最大感知失真。这种主观冗余去除方法包括幅度非线性和人类感知的一些时间特征。还从该模型推导出了自适应运动估计算法的感知加权控制。运动估计中的感知反馈确保了运动估计工作量与冗余去除过程之间的感知平衡。结果表明,这种反馈引发了一种尺度相关的细化策略,产生了更稳健且有意义的运动估计,这可能有助于更高级别的序列解释。感知上有意义的失真度量和重建帧显示了所提方案相对于具有未加权运动估计和类似MPEG量化的H.263方案在主观上的改进。