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Mixed-resolution Wyner-Ziv video coding based on selective data pruning

机译:基于选择性数据修剪的混合分辨率Wyner-Ziv视频编码

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In current distributed video coding (DVC), interpolation is performed at the decoder and the interpolated pixels are reconstructed by using error-correcting codes, such as Turbo codes and LDPC. There are two possibilities for downsampling video sequences at the encoder: temporally or spatially. Traditionally temporal downsampling, i.e., frame dropping, is used for DVC. Furthermore, those with spatial downsampling (scaling) have been investigated. Unfortunately, most of them are based on uniform downsampling. Due to this, details in video sequences are often discarded. For example, edges and textured regions are difficult to interpolate, and thus require many parity bits to restore the interpolated portions for the spatial domain DVC. In this paper, we propose a new spatial domain DVC based on adaptive line dropping so-called selective data pruning (SDP). SDP is a simple nonuniform downsampling method. The pruned lines are determined to avoid cutting across edges and textures. Experimental results show the proposed method outperforms a conventional DVC for sequences with a large amount of motions.
机译:在当前的分布式视频编码(DVC)中,在解码器处执行内插,并且通过使用诸如Turbo码和LDPC的纠错码来重构内插像素。在编码器上对视频序列进行下采样有两种可能性:时间上或空间上。传统上,将时间下采样(即,帧丢失)用于DVC。此外,已经对具有空间下采样(缩放)的图像进行了研究。不幸的是,它们大多数基于统一的下采样。因此,通常会丢弃视频序列中的细节。例如,边缘和纹理区域难以插值,因此需要许多奇偶校验位来恢复空间域DVC的插值部分。在本文中,我们提出了一种基于自适应行删除的新的空间域DVC,即所谓的选择性数据修剪(SDP)。 SDP是一种简单的非均匀下采样方法。确定修剪后的线条以避免割破边缘和纹理。实验结果表明,对于具有大量运动的序列,该方法优于传统的DVC。

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