Improved Screen Content Coding in VVC Using Soft Context Formation

TL;DR

It is shown that pixel-wise lossless coding can outperform lossy VVC coding in such areas and achieve Bjontegaard-Delta-rate gains of 4.98% on the evaluated data sets compared to VVC.

Abstract

Screen content images typically contain a mix of natural and synthetic image parts. Synthetic sections usually are comprised of uniformly colored areas and repeating colors and patterns. In the VVC standard, these properties are exploited using Intra Block Copy and Palette Mode. In this paper, we show that pixel-wise lossless coding can outperform lossy VVC coding in such areas. We propose an enhanced VVC coding approach for screen content images using the principle of soft context formation. First, the image is separated into two layers in a block-wise manner using a learning-based method with four block features. Synthetic image parts are coded losslessly using soft context formation, the rest with VVC.We modify the available soft context formation coder to incorporate information gained by the decoded VVC layer for improved coding efficiency. Using this approach, we achieve Bjontegaard-Delta-rate gains of 4.98% on the evaluated data sets compared to VVC.

Figures (5)

• Figure 1: Block diagram of the SCF method with its three stages.
• Figure 2: Context pattern: If the values in the template $\{A,B, \dots, F\}$ are similar to $\{A',B', \dots, F'\}$, then the current value at position $X$ is likely to be similar to the value at $X'$.
• Figure 3: Image segmented block-wise into separate layers coded by the VVC and the SCF coder for QP 22. Grayed out areas indicate pixels to be encoded in the SCF layer.
• Figure 4: Block diagrams of the encoding and decoding process of the proposed method.
• Figure 5: Rate-distortion curve averaged over all test sets with respect to the PSNR for the proposed method and the original VTM 17.2.