Adaptive quantization proves to be an effective tool to improve coding performance. In this paper, we propose an adaptive spatiotemporal perception aware quantization algorithm to increase subjective coding performance. To measure the spatiotemporally perceptual redundancy, the perceptual complexity models are firstly established with spatial and temporal characteristics respectively. With the help of the models, the adaptive spatial and temporal quantization parameter (QP) offsets are then calculated for each coding tree unit (CTU), respectively. Finally, the perceptually optimal Lagrange multiplier of each CTU is determined with the spatial–temporal QP offset. Experimental results show that the proposed algorithm reduces 8.6% and 8.4% Bjontegaard-Delta Rate (BD-Rate) with Structural Similarity Index Metric (SSIM) in average over the second generation of Audio Video Coding Standard (AVS2) reference software RD17.0 in Low-Delay-P (LDP) and Random-Access (RA) configurations, respectively. The subjective assessment proves that the proposed algorithm can reduce the bitrates with the same subjective quality significantly.

自适应量化被证明是提高编码性能的有效工具。在本文中，我们提出了一种自适应的时空感知感知量化算法，以提高主观编码性能。为了测量时空感知冗余，首先建立了具有时空特征的感知复杂度模型。然后，借助模型，分别为每个编码树单元（CTU）计算自适应空间和时间量化参数（QP）偏移。最后，每个CTU的感知最佳拉格朗日乘数由时空QP偏移确定。实验结果表明，该算法减少了8.6％和8。低延迟-P（LDP）和随机-第二代音频视频编码标准（AVS2）参考软件RD17.0中具有结构相似性指标度量（SSIM）的平均4％约恩加德河三角洲速率（BD-Rate）分别访问（RA）配置。主观评估表明，所提算法可以在相同主观质量的情况下显着降低比特率。