基于选择性数据修剪的混合分辨率Wyner-Ziv视频编码

T. Phan, Yuichi Tanaka, Madoka Hasegawa, Shigeo Kato
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引用次数: 3

摘要

在当前的分布式视频编码(DVC)中,在解码器处进行插值,并使用纠错码(如Turbo码和LDPC码)重建插值后的像素。在编码器下采样视频序列有两种可能:时间上的或空间上的。传统上,时间下采样,即丢帧,用于DVC。此外,还研究了空间下采样(缩放)的情况。不幸的是,它们中的大多数都是基于均匀下采样。因此,视频序列中的细节常常被丢弃。例如,边缘和纹理区域很难插值,因此需要许多奇偶校验位来恢复空间域DVC的插值部分。本文提出了一种新的基于自适应丢线的空间域DVC,即选择性数据修剪(SDP)。SDP是一种简单的非均匀下采样方法。修剪的线条是确定的,以避免切割跨边缘和纹理。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方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mixed-resolution Wyner-Ziv video coding based on selective data pruning
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.
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