基于Lloyd算法的三维视频深度图量化

Zhi Jin, T. Tillo, Jimin Xiao, Fei Cheng
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引用次数: 1

摘要

基于深度图的三维视图合成技术允许对相同的三维内容合成不同的虚拟视角,而这些虚拟视角的逼真三维视图感知高度依赖于深度信息的准确性。因此,纵深图虽然不是用户看到的,但其质量直接影响到三维变形合成的虚拟视图的质量。鉴于目前深度图采集技术的进展,为了保持与不同编码标准的兼容性,需要对深度值进行量化,以便表示为实用方便的值。然而,量化过程会导致深度图失真。为了减少这种负面影响,本文提出了一种新的量化方法,该方法综合考虑了深度值的分布和三维渲染过程,从而最大限度地减少了深度图引起的渲染失真。实验结果表明,与传统的非均匀量化方法相比,该量化方法对不同序列的信噪比增益从1dB提高到14dB。
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3-D video depth map quantization based on Lloyd's algorithm
Depth map based 3-D view synthesis technique allows to synthesize different virtual perspectives of the same 3-D content, and the lifelike 3-D view perception of these virtual perspectives is highly depending on the accuracy of depth information. So, although depth map is not viewed by the users, however, its quality directly affects that of the synthesized virtual views by the 3-D warping process. In view of current progress in depth map acquisition techniques, and in order to maintain compatibility with different encoding standards depth values need to undergo quantization, so as to be represented at practical and convenient values. However, the quantization process causes depth map distortion. In order to reduce this negative effect, this paper propose a new quantization method which jointly considers the distribution of depth values and the 3-D rendering process, so as to minimize the depth map induced rendering distortion. The experimental results with the proposed quantization method indicate that the SNR gain has increased from 1dB to 14dB for different sequences when compared with the traditional non-uniform quantization method.
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