Department of Photonics Engineering, Technical University of Denmark, Lyngby 2800, Denmark.
IEEE Trans Image Process. 2012 Dec;21(12):4782-96. doi: 10.1109/TIP.2012.2215621. Epub 2012 Aug 27.
Distributed video coding (DVC) is a coding paradigm that exploits the source statistics at the decoder side to reduce the complexity at the encoder. The coding efficiency of DVC critically depends on the quality of side information generation and accuracy of noise modeling. This paper considers transform domain Wyner-Ziv (TDWZ) coding and proposes using optical flow to improve side information generation and clustering to improve the noise modeling. The optical flow technique is exploited at the decoder side to compensate for weaknesses of block-based methods, when using motion-compensation to generate side information frames. Clustering is introduced to capture cross band correlation and increase local adaptivity in the noise modeling. This paper also proposes techniques to learn from previously decoded WZ frames. Different techniques are combined by calculating a number of candidate soft side information for low density parity check accumulate decoding. The proposed decoder side techniques for side information and noise learning (SING) are integrated in a TDWZ scheme. On test sequences, the proposed SING codec robustly improves the coding efficiency of TDWZ DVC. For WZ frames using a GOP size of 2, up to 4-dB improvement or an average (Bjøntegaard) bit-rate savings of 37% is achieved compared with DISCOVER.
分布式视频编码（DVC）是一种利用解码器端源统计信息来降低编码器复杂度的编码范式。DVC 的编码效率严重依赖于辅助信息生成的质量和噪声建模的准确性。本文考虑变换域 Wyner-Ziv（TDWZ）编码，并提出使用光流来改进辅助信息生成，使用聚类来改进噪声建模。在使用运动补偿生成辅助信息帧时，光流技术在解码器端被用来弥补基于块的方法的弱点。聚类被引入以捕获跨带相关性并提高噪声建模中的局部适应性。本文还提出了从以前解码的 WZ 帧中学习的技术。不同的技术通过计算用于低密度奇偶校验累积解码的多个候选软辅助信息来组合。所提出的用于辅助信息和噪声学习（SING）的解码器端技术被集成到 TDWZ 方案中。在测试序列上，所提出的 SING 编解码器稳健地提高了 TDWZ DVC 的编码效率。对于 GOP 大小为 2 的 WZ 帧，与 DISCOVER 相比，可获得高达 4dB 的增益或平均（Bjøntegaard）比特率节省 37%。
