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Hierarchical Hole-Filling(HHF): Depth image based rendering without depth map filtering for 3D-TV

机译:分层补漏(HHF):基于深度图像的渲染,无需3D-TV的深度图过滤

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In this paper we propose a new approach for disocclusion removal in depth image-based rendering (DIBR) for 3D-TV. The new approach, Hierarchical Hole-Filling (HHF), eliminates the need for any preprocessing of the depth map. HHF uses a pyramid like approach to estimate the hole pixels from lower resolution estimates of the 3D wrapped image. The lower resolution estimates involves a pseudo zero canceling plus Gaussian filtering of the wrapped image. Then starting backwards from the lowest resolution hole-free estimate in the pyramid, we interpolate and use the pixel values to fill in the hole in the higher up resolution image. The procedure is repeated until the estimated image is hole-free. Experimental results show that HHF yields virtual images that are free of any geometric distortions, which is not the case in other algorithms that preprocess the depth map. Experiments has also shown that unlike previous DIBR techniques, HHF is not sensitive to depth maps with high percentage of bad matching pixels.
机译:在本文中,我们提出了一种在3D-TV的基于深度图像的渲染(DIBR)中去除遮挡的新方法。新方法“分层空穴填充(HHF)”消除了对深度图进行任何预处理的需要。 HHF使用金字塔式方法从3D包裹的图像的较低分辨率估算中估算空洞像素。较低的分辨率估计值包括伪零消除和包裹图像的高斯滤波。然后从金字塔中最低分辨率的无孔估计开始倒退,我们进行插值并使用像素值填充较高分辨率的图像中的孔。重复该过程,直到估计的图像没有孔为止。实验结果表明,HHF生成的虚拟图像没有任何几何失真,而其他预处理深度图的算法则不是这种情况。实验还表明,与以前的DIBR技术不同,HHF对具有高百分比的不良匹配像素的深度图不敏感。

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