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Incremental-LDI for multi-view coding

机译:增量LDI用于多视图编码

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This paper describes an Incremental algorithm for Layer Depth Image construction (I-LDI) from multi-view plus depth data sets. A solution to sampling artifacts is proposed, based on pixel interpolation (inpainting) restricted to isolated unknown pixels. A solution to ghosting artifacts is also proposed, based on a depth discontinuity detection, followed by a local foreground/background classification. We propose a formulation of warping equations which reduces time consumption, specifically for LDI warping. Tests on Break-dancers and Ballet MVD data sets show that extra layers in I-LDI contain only 10% of first layer pixels, compared to 50% for LDI. I-LDI Layers are also more compact, with a less spread pixel distribution, and thus easier to compress than LDI Visual rendering is of similar quality with I-LDI and LDI.
机译:本文介绍了一种基于多视图和深度数据集的层深度图像构造(I-LDI)增量算法。基于限于孤立的未知像素的像素插值(修复),提出了一种采样伪影的解决方案。还提出了一种基于深度不连续检测的重影伪影解决方案,然后进行局部前景/背景分类。我们提出了一种翘曲方程式,可以减少时间消耗,特别是用于LDI翘曲。对霹雳舞者和芭蕾舞MVD数据集的测试表明,I-LDI中的额外层仅包含第一层像素的10%,而LDI仅为50%。 I-LDI层也更紧凑,像素分布更少,因此与LDI相比更易于压缩。I-LDI和LDI的视觉渲染质量相似。

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