针对高动态范围(HDR) 视频较之于传统低动态范围(LDR) 视频所需存储资源和传输带宽急剧增加的问题，本文提出了一种基于视觉感知特性的HDR 视频编码的动态率失真优化算法，以提高高效视频编码(HEVC) Main 10 编码HDR 视频的性能。本文通过引入视觉选择性关注信息，对不同区域采取非均等的失真权重分配策略，优化常规的失真计算方法；同时，为了进一步去除视频中的感知冗余，融合视频内容的纹理特性自适应调节拉格朗日乘子，并应用于编码量化器动态调节量化参数，实现编码比特和失真感知权衡。实验结果表明：与HEVC Main 10 相比，在相同HDR-VDP 和PSNR DE 质量指标下，所提算法平均节省7.46% 和6.53% 码率，最大分别节省18.52% 和11.49%，所提算法在保持视觉质量的前提下能够有效降低码率。

In view of the drastic increase of storage resources and transmission bandwidth requirement for high dynamic range (HDR) video compared to the traditional low dynamic range (LDR) video, we propose a dynamic rate distortion optimization algorithm based on visual perception for HDR Video encoding to improve the performance of high efficiency video coding (HEVC) Main 10 for coding HDR video. With the information of visual selective attention, we design a non-uniform distortion weight distribution strategy to different regions of interest and improve the conventional method of distortion calculation. At the same time, in order to further eliminate the perceptive redundancy in HDR video coding, the texture characteristics of video content are used to adjust Lagrange multipliers adaptively, which is applied to the encoder to dynamically adjust the quantization parameters to realize reasonably the trade-off between coded bits and distortion perception. The experimental results show that the proposed algorithm can save an average of 7.46% and 6.53% bitrate with the same HDR-visible difference predictor-2.2(HDR-VDP-2.2 ) and PSNR_DE compared with HEVC Main 10, saving the maximum of 18.52 % and 11.49% respectively. The proposed algorithm can effectively reduce the consumption of the overall bitrates and still maintain the visual quality of the reconstructed HDR video.