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DENSE DISPARITY ESTIMATION IN A MULTI-VIEW DISTRIBUTED VIDEO CODING SYSTEM

机译:多视图分布式视频编码系统中的密集差异估计

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Distributed video coding (DVC) is a recent paradigm which aims at transferring part of the coding complexity from the encoder to the decoder. The performance of such a coding scheme strongly depends on the capacity to estimate correlation at the decoder and, consequently, on the side information quality. In this paper we consider a multi-view DVC framework and propose a very efficient dense disparity estimation technique for side information construction, based on a variational formulation. The simulation results show that our approach clearly outperforms the existing methods for inter-view side-information generation.
机译:分布式视频编码(DVC)是最近的范式,其目的在于将部分编码复杂度传输到解码器到解码器。这种编码方案的性能强烈取决于估计解码器在解码器中的相关的能力,并且因此,在侧面信息质量上。本文考虑了一种多视图DVC框架,并基于变分制剂提出了一种非常有效的侧信息结构的密集视差估计技术。仿真结果表明,我们的方法显然优于View侧面信息生成的现有方法。

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