Adaptive Resolution Change Using Uncoded Areas and Dictionary Learning-Based Super-Resolution in Versatile Video Coding
Adaptive Resolution Change Using Uncoded Areas and Dictionary Learning-Based Super-Resolution in Versatile Video Coding
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DOI：
10.1109/icassp40776.2020.9054522
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发表时间：
2020-05
期刊：
影响因子：
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通讯作者：
J. Schneider;Johannes Sauer;Christian Rohlfing
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文献类型：
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作者：
J. Schneider;Johannes Sauer;Christian Rohlfing
视频编码中的自适应分辨率改变（ARC）的概念已经从诸如MPEG-4的以前的国际标准中得知[1]。然而，在MPEG-4中，线性滤波器用于上采样，这对于以不同分辨率编码视频至关重要。随着基于机器学习的超分辨率方法在过去十年中的兴起，开发了优于传统上采样方法的强大算法。这一贡献介绍了一个ARC的概念，使用未编码的区域内的一帧视频序列和字典学习（DL）为基础的超分辨率（SR）计划。在这个概念中，帧包含不同分辨率级别的图片，这些图片通过使用切片和瓦片在空间上分离。通常，瓷砖可以标记为编码或未编码。从比特流中省略不保持任何编码区块的切片。因此，仅一个分辨率级别需要被编码，而另一个分辨率级别在解码器侧生成。在编码器处，进行率失真判定以便判定应当对哪个分辨率级别进行编码。仿真结果表明，相对于开发中的通用视频编码（VVC）标准的增益可以在低比特率实现。
The concept of Adaptive Resolution Change (ARC) in video coding is already known from former international standards such as MPEG-4 [1]. However, in MPEG-4 linear filters are used for upsampling, which is crucial to coding video at varying resolution. With the rise of machine learning-based super-resolution methods in the last decade, powerful algorithms outperforming conventional upsampling methods were developed. This contribution introduces an ARC concept using un-coded areas within a frame of a video sequence and a Dictionary Learning (DL)-based Super-Resolution (SR) scheme. In this concept, a frame contains a picture at different resolution levels, which are spatially separated by the use of slices and tiles. Generally, a tile can be marked as coded or un-coded. Slices which do not hold any coded tiles are omitted from the bitstream. Thus, only one resolution level needs to be coded, while the other is generated at the decoder side. At the encoder a rate-distortion decision is made in order to decide, which resolution level should be coded. Simulation results show that gains with respect to the Versatile Video Coding (VVC) standard in development can be achieved at low bitrates.