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

机译:利用基于多分辨率图的转换进行深度映射压缩,用于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格式的3D视觉数据的高效网络传输是重要的,其中观察者可以通过接收的相邻纹理和深度映射来合成基于深度图像的渲染(DIBR)的自由所选择的视点的图像作为锚点。与纹理地图不同,深度图表现出独特的特性,如平滑的内表面和可以利用用于编码增益的锋利边缘。在本文中,我们提出了一种使用先前提出的基于图形的变换(GBT)进行深度映射压缩的多分辨率方法。关键的想法是单独处理大代码块的平滑表面和尖锐边缘,并以不同的分辨率对它们进行编码:在原始高分辨率(HR)中的编码边缘以保持清晰度,并在低通滤波和下水中编码平滑表面低分辨率(LR)以保存编码位。由于GBT在编码光滑表面深度映射时产生小型或零高频分量,并且导致变换域中的紧凑型表示,因此在编码时产​​生小或零高频分量。通过在LR GBT中编码下采样的表面区域,我们实现了大块的表示紧凑性,而没有与自适应大块GBT相关的高计算复杂度。在解码器处,在保留编码的HR边缘时,编码的LR表面被上采样并内插。实验结果表明,与DCT编码原始HR Depth Maps的DCT intrA的Native H.264 Intra,我们使用GBT的提出的多分辨率方法将比特率降低68%,与编码小块的单分辨率GBT相比,55%。

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