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Adaptive view synthesis optimization for low complexity 3D-HEVC encoding

机译:低复杂度3D-HEVC编码的自适应视图综合优化

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Depth compression plays an important role in 3D video coding with the typical texture-plus-depth representation. In this paper, to reduce the encoding complexity of depth map, we propose a low complexity adaptive View Synthesis Optimization scheme for the 3D extension of high efficiency video coding (3D-HEVC) standard. More specifically, we distinguish the coding tree units (CTUs) based on the influence of depth map compression on the quality of rendered synthesized view, and classify them into two categories, including synthesized view distortion change (SVDC) based and view synthesis distortion estimation (VSDE) based CTUs. In this manner, we can dynamically distinguish the CTUs and apply different rate-distortion optimization strategies. Moreover, for VSDE based CTUs, a new distortion model is proposed to infer the distortion of the synthesized view based on the depth distortion and texture characteristics. As such, we can achieve a good trade-off between the rate-distortion performance and computational complexity for depth map coding. Experimental results also confirm that the proposed scheme is effective in reducing the encoding complexity with ignorable rate-distortion performance loss compared with the state-of-the-art scheme in the 3D-HEVC platform. (C) 2018 Elsevier Ltd. All rights reserved.
机译:深度压缩在具有典型的纹理加深度表示的3D视频编码中起着重要作用。在本文中,为了降低深度图的编码复杂度,我们针对高效视频编码(3D-HEVC)标准的3D扩展提出了一种低复杂度的自适应视图综合优化方案。更具体地说,我们根据深度图压缩对渲染的合成视图质量的影响来区分编码树单元(CTU),并将其分为两类,包括基于合成视图失真变化(SVDC)和视图合成失真估计( VSDE)的CTU。通过这种方式,我们可以动态区分CTU,并应用不同的速率失真优化策略。此外,对于基于VSDE的CTU,提出了一种新的变形模型,基于深度变形和纹理特征来推断合成视图的变形。这样,我们可以在深度图编码的速率失真性能和计算复杂度之间取得良好的平衡。实验结果还证实,与3D-HEVC平台中的最新方案相比,该方案在降低编码复杂度和可忽略的速率失真性能损失方面是有效的。 (C)2018 Elsevier Ltd.保留所有权利。

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