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Depth coding using depth discontinuity prediction and in-loop boundary reconstruction filtering

机译:使用深度不连续性预测和环内边界重构滤波的深度编码

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摘要

This paper presents a depth coding strategy that employs K-means clustering to segment the sequence of depth images into K clusters. The resulting clusters are losslessly compressed and transmitted as supplemental enhancement information to aid the decoder in predicting macroblocks containing depth discontinuities. This method further employs an in-loop boundary reconstruction filter to reduce distortions at the edges. The proposed algorithm was integrated within both H.264/AVC and H.264/MVC video coding standards. Simulation results demonstrate that the proposed scheme outperforms the state of the art depth coding schemes, where rendered Peak Signal to Noise Ratio (PSNR) gains between 0.1 dB and 0.5 dB were observed.
机译:本文提出了一种深度编码策略,该策略采用K-means聚类将深度图像序列分割为K个聚类。得到的簇被无损压缩并作为补充增强信息发送,以帮助解码器预测包含深度不连续性的宏块。该方法还采用环路内边界重构滤波器来减少边缘的失真。所提出的算法已集成到H.264 / AVC和H.264 / MVC视频编码标准中。仿真结果表明,所提出的方案优于现有的深度编码方案,在该方案中,观察到的峰值信噪比(PSNR)增益在0.1 dB和0.5 dB之间。

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