率失真优化技术在视频编码中占据着重要位置, 传统的率失真优化技术从信号处理的角度来度量重建视频的失真, 未充分考虑到人的视觉感知特性. 为了得到更好的压缩性能, 提出了一种利用视觉感知特性的动态率失真优化方法. 该方法采用更符合人的视觉特性的基于结构相似性的失真度量方法代替常规的失真度量方法, 构建了新的率失真优化模型; 同时, 引入了人的选择性关注度信息, 对不同关注区域采取非均等的资源分配策略, 用表征视频内容的特征量来动态调节拉格朗日率失真乘数, 在保证视觉质量的前提下更合理地分配有限的码率资源. 实验结果表明, 在重建视频的视觉质量相当的条件下, 文中的方法能够有效地节省视频编码的码率.
In the conventional rate distortion optimization (RDO) video coding, the measure of distortion is mainly from the perspective of signal processing, while dose not fully take into account the characteristics of visual perception. In this paper, in order to establish a RDO model which is more consistent with the human visual perception, we introduce the structural similarity and the content saliency information into the distor-tion metric. An adaptive Lagrange multiplier selection scheme is presented to allocate the bit resources more rationally by keeping the balance of the bit-rate and the visual quality. Experimental results show that the proposed method can reduce bit-rate effectively under equal visual quality.