为AV1非矩形块变换设计高效熵编码，提升压缩率。
Entropy Coding for Non-Rectangular Transform Blocks using Partitioned DCT Dictionaries for AV1
- 用分块DCT字典实现非矩形块的稀疏表示
- 理论码率降低显著，尤其在与DCT差异大时
- 仅需小改动解码器，适合视频编码优化
近期视频编码标准如VVC和AV1采用非矩形（NR）分区，通过边界平滑融合预测信号，并对整块进行矩形变换。目前尚不支持非矩形信号变换。一种将相同分区应用于二维离散余弦变换（DCT）基底，并在该字典中寻找非矩形信号稀疏表示的方法，在参考软件外的实验中表现出良好增益。该方法在解码端使用常规逆变换重建矩形信号，并丢弃感兴趣区域外内容。此设计因解码端改动极小而具有吸引力。然而，现有熵编码方案对这类系数编码效率不高，因其主要针对标准DCT系数设计。本文提出一种新型熵编码方法，能有效建模这些变换系数的特性，实现显著的理论码率节省，基于条件熵估算，尤其在与DCT差异较大的场景中表现突出。
原文摘要 · Abstract (English)
Recent video codecs such as VVC and AV1 apply a Non-rectangular (NR) partitioning to combine prediction signals using a smooth blending around the boundary, followed by a rectangular transform on the whole block. The NR signal transformation is not yet supported. A transformation technique that applies the same partitioning to the 2D Discrete Cosine Transform (DCT) bases and finds a sparse representation of the NR signal in such a dictionary showed promising gains in an experimental setup outside the reference software. This method uses the regular inverse transformation at the decoder to reconstruct a rectangular signal and discards the signal outside the region of interest. This design is appealing due to the minimal changes required at the decoder. However, current entropy coding schemes are not well-suited for optimally encoding these coefficients because they are primarily designed for DCT coefficients. This work introduces an entropy coding method that efficiently codes these transform coefficients by effectively modeling their properties. The design offers significant theoretical rate savings, estimated using conditional entropy, particularly for scenarios that are more dissimilar to DCT in an experimental setup.
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