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Depth map compression using multi-resolution graph-based transform for depth-image-based rendering

机译:使用基于多分辨率图的变换进行深度图压缩以进行基于深度图像的渲染

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Depth map compression is important for efficient network transmission of 3D visual data in texture-plus-depth format, where the observer can synthesize an image of a freely chosen viewpoint via depth-image-based rendering (DIBR) using received neighboring texture and depth maps as anchors. Unlike texture maps, depth maps exhibit unique characteristics like smooth interior surfaces and sharp edges that can be exploited for coding gain. In this paper, we propose a multi-resolution approach to depth map compression using previously proposed graph-based transform (GBT). The key idea is to treat smooth surfaces and sharp edges of large code blocks separately and encode them in different resolutions: encode edges in original high resolution (HR) to preserve sharpness, and encode smooth surfaces in low-pass-filtered and down-sampled low resolution (LR) to save coding bits. Because GBT does not filter across edges, it produces small or zero high-frequency components when coding smooth-surface depth maps and leads to a compact representation in the transform domain. By encoding down-sampled surface regions in LR GBT, we achieve representation compactness for a large block without the high computation complexity associated with an adaptive large-block GBT. At the decoder, encoded LR surfaces are up-sampled and interpolated while preserving encoded HR edges. Experimental results show that our proposed multi-resolution approach using GBT reduced bitrate by 68% compared to native H.264 intra with DCT encoding original HR depth maps, and by 55% compared to single-resolution GBT encoding small blocks.
机译:深度图压缩对于以纹理加深度格式进行3D可视数据的有效网络传输非常重要,其中观察者可以使用接收到的相邻纹理和深度图,通过基于深度图像的渲染(DIBR)来合成自由选择的视点的图像。作为锚点。与纹理贴图不同,深度贴图具有独特的特征,例如光滑的内表面和锋利的边缘,可用于编码增益。在本文中,我们提出了一种使用先前提出的基于图的变换(GBT)的深度图压缩多分辨率方法。关键思想是分别处理大型代码块的平滑表面和尖锐边缘,并以不同的分辨率对其进行编码:以原始高分辨率(HR)编码边缘以保持清晰度,并以低通滤波和下采样的形式编码平滑表面低分辨率(LR)以节省编码位。由于GBT不会跨边缘过滤,因此在编码平滑表面深度图时会产生很小的高频分量或零高频分量,并导致变换域中的紧凑表示。通过在LR GBT中对下采样的表面区域进行编码,我们实现了大块的表示紧凑性,而没有与自适应大块GBT相关的高计算复杂性。在解码器处,对编码的LR表面进行上采样和内插,同时保留编码的HR边缘。实验结果表明,与使用DCT编码原始HR深度图的原始H.264帧相比,我们提出的使用GBT的多分辨率方法将比特率降低了68%,而与对小块进行单分辨率的GBT编码相比,则将比特率降低了55%。

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