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Efficient depth video coding based on view synthesis distortion estimation

机译:基于视图合成失真估计的高效深度视频编码

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An efficient coding algorithm for depth map images and videos, based on view synthesis distortion estimation, is proposed in this work. We first analyze how a depth error is related to a disparity error and how the disparity vector error affects the energy spectral density of a synthesized color video in the frequency domain. Based on the analysis, we propose an estimation technique to predict the view synthesis distortion without requiring the actual synthesis of intermediate view frames. To encode the depth information efficiently, we employ a Lagrangian cost function to minimize the view synthesis distortion subject to the constraint on a transmission bit rate. In addition, we develop a quantization scheme for residual depth data, which adaptively assigns bits according to block complexities. Simulation results demonstrate that the proposed depth video coding algorithm provides significantly better R-D performance than conventional algorithms.
机译:提出了一种基于视图合成失真估计的深度图图像和视频编码方法。我们首先分析深度误差与视差误差之间的关系,以及视差矢量误差如何在频域中影响合成彩色视频的能谱密度。在此基础上,我们提出了一种估计技术,可以在不需要实际合成中间视图帧的情况下预测视图合成失真。为了有效地对深度信息进行编码,我们采用拉格朗日成本函数来最小化受传输比特率约束的视图合成失真。此外,我们针对残留深度数据开发了一种量化方案,该方案根据块的复杂性自适应地分配位。仿真结果表明,提出的深度视频编码算法比常规算法具有更好的R-D性能。

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