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PATCH-AWARE AVERAGING FILTER FOR SCALING IN POINT CLOUD COMPRESSION

机译:针对点云压缩中的缩放的补丁感知平均滤波器

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With the development of augmented reality, the delivery and storage of 3D content have become an important research area. Among the proposals for point cloud compression collected by MPEG, Apple's Test Model Category 2 (TMC2) achieves the highest quality for 3D sequences under a bitrate constraint. However, the TMC2 framework is not spatially scalable. In this paper, we add interpolation components which make TMC2 suitable for flexible resolution. We apply a patch-aware averaging filter to eliminate most outliers which result from the interpolation. Experimental results show that our method performs well both on objective evaluation and visual quality.
机译:随着增强现实的发展,3D内容的交付和存储已成为一个重要的研究区域。在由MPEG收集的点云压缩的提案中,Apple的测试模型2(TMC2)在比特率约束下实现了3D序列的最高质量。但是,TMC2框架在空间上不可扩展。在本文中,我们添加了用于使TMC2适用于灵活分辨率的插值组件。我们应用补丁感知平均过滤器,以消除由插值产生的大多数异常值。实验结果表明,我们的方法在客观评价和视觉质量方面表现良好。

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