论文标题
优化用于屏幕内容剩余编码的概率分布
Optimization of Probability Distributions for Residual Coding of Screen Content
论文作者
论文摘要
概率分布建模是大多数竞争性方法的基础，用于屏幕内容的无损编码。一种这样的最新方法称为软上下文形成（SCF）。对于每个像素要编码，根据相邻模式和已经编码的图像中的该模式估算概率分布。使用算术编码器，可以非常有效地对像素颜色进行编码，前提是在与类似模式相关联之前已经观察到当前颜色。如果不是这种情况，则使用调色板对颜色进行编码，或者（如果仍然未知）通过剩余编码进行编码。基于调色板的编码和剩余编码的压缩效率明显比基于软上下文形成的编码要差。在本文中，通过自适应修剪剩余误差的概率分布来改善剩余编码阶段。此外，提出了一种增强的概率建模，用于指示新颜色，具体取决于附近的新颜色的发生。这些修改导致比特率平均降低2.9％。与HEVC（HM-16.21 + SCM-8.8）和FLIF相比，改进的SCF方法平均节省了约11％和18％的速率。
Probability distribution modeling is the basis for most competitive methods for lossless coding of screen content. One such state-of-the-art method is known as soft context formation (SCF). For each pixel to be encoded, a probability distribution is estimated based on the neighboring pattern and the occurrence of that pattern in the already encoded image. Using an arithmetic coder, the pixel color can thus be encoded very efficiently, provided that the current color has been observed before in association with a similar pattern. If this is not the case, the color is instead encoded using a color palette or, if it is still unknown, via residual coding. Both palette-based coding and residual coding have significantly worse compression efficiency than coding based on soft context formation. In this paper, the residual coding stage is improved by adaptively trimming the probability distributions for the residual error. Furthermore, an enhanced probability modeling for indicating a new color depending on the occurrence of new colors in the neighborhood is proposed. These modifications result in a bitrate reduction of up to 2.9% on average. Compared to HEVC (HM-16.21 + SCM-8.8) and FLIF, the improved SCF method saves on average about 11% and 18% rate, respectively.
