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收稿：2019-11-09，
修回：2020-5-13，
录用：2020-5-20，
纸质出版：2021-02-16
移动端阅览
目的
2
随着云计算和移动互联网技术的飞速发展，屏幕图像编码已成为视频压缩领域新的研究热点。帧内块复制（intra block copy，IBC）算法是屏幕内容编码（screen content coding，SCC）中的核心算法，已经成为高效视频编码（high efficiency video coding，HEVC）等标准中屏幕内容编码的重要组成部分。为了进一步消除IBC算法中的位移矢量（displacement vector，DV）参数编码的冗余，根据DV参数具有的固有帧内块匹配特性和相关性，提出了一种DV参数编码算法。
方法
2
首先，对待编码DV采用邻近块与最近块相结合的DV预测编码方案，进一步提高DV的预测编码效率；然后，对预测编码效率不高的DV，提出了一种基于区域划分与调整的高效DV直接编码方案。对SCC标准测试数据集合中的17个测试数据集合的3种编码配置从编码效率和复杂度两方面进行了评测。
结果
2
实验结果表明，对于SCC标准测试数据集合中移动的文字和图形序列类别，在全帧内、随机接入和低延迟这3种有损编码配置下，提出的DV算法与HEVC SCC中的IBC算法相比，在编解码复杂度没有任何影响的前提下，
Y
分量的BD（Bjφntegaard Delta）-rate平均降低率分别为1.04%、0.87%和0.93%，全帧内配置下
Y
分量的BD-rate降低率可达2.99%。
结论
2
本文方法优于HEVC-SCC中的IBC算法中的DV编码算法，能有效提升编码效率。
Objective
2
With the recent rapid development of technologies in cloud computing and mobile internet
screen content coding (SCC) has become a key technology in many popular applications
such as videoconferencing with document or slide sharing
remote desktop
screen sharing
mobile or external display interfacing
and cloud gaming. Typical computer screen content contains a mixture of camera-captured and screen contents. Screen content exhibits highly different characteristics and varied levels of human's visual sensitivity to distortion compared with traditional camera-captured content. Screen content videos are typically not noisy
with sharp edges and multiple repeated patterns. New coding tools for better utilizing the correlation characteristics of screen content are necessary. Accordingly
SCC has become a popular topic in multimedia applications in recent years and has elicited increasing research attention from academia and industry. Several international video coding standards include efficient SCC capability
such as high efficiency video coding (HEVC)
versatile video coding (VVC)
and second-generation and third-generation audio video coding standard (AVS2 and AVS3
respectively). Repeated identical patterns (i.e.
matching patterns) are frequently observed on the same picture of screen content. Two major SCC tools in HEVC SCC were developed in recent years to utilize these repeated identical patterns with a variety of sizes and shapes. These tools are intra block copy (IBC) and palette coding. IBC
also called intra picture block compensation or current picture referencing
is a highly efficient technique for improving coding performance. It is effective for coding repeated identical patterns with a few fixed sizes and shapes. IBC is a direct extension of the traditional inter-prediction technique for the current picture
wherein a current prediction block is predicted from a reference block located in the already reconstrcted regions of the same picture. IBC has been adopted in the HEVC SCC extensions
VVC
and AVS3. In IBC
a displacement vector (DV) is used to signal the relative displacement from the position of the current block to that of the reference block. The coding efficiency of IBC primarily depends on the coding efficiency of DV. The existing DV coding algorithm used in HEVC SCC is the same as the motion vector coding algorithm used in the inter-prediction scheme. However
the existing DV coding algorithm only utilizes the correlations among the DVs of neighboring blocks. Moreover
intra block and inter block matching characteristics exhibit numerous differences. Thus
in accordance with the inherent intra block matching characteristics and different correlations of DV parameters in the IBC algorithm
we propose an improved DV algorithm for further increasing the coding efficiency of IBC.
Method
2
The DV to be coded has been proven to exhibit numerous correlations not only with neighboring blocks but also with recently coded blocks. To utilize the correlations of DVs with neighboring and recently coded blocks
we first apply an improved DV coding algorithm that adaptively uses DV predictions from either neighboring or recently coded blocks. Second
a direct DV coding scheme that uses a DV region division algorithm and a DV adjusting algorithm is proposed to eliminate redundancies further in the existing DV coding algorithm. Lastly
we evaluate coding performance and complexity on 17 test datasets from the SCC standard test dataset with three encoding configurations. In particular
13 sequences are selected to represent the most common screen content videos
referred to as the "text and graphics with motion" (TGM) category
and 4 sequences are selected to represent a mixture of natural video and text/graphics
referred to as the "mixed content" category.
Result
2
Experimental results show that the proposed algorithm achieves average
Y
BD-rate reductions of up to 1.04%
0.87%
and 0.93% for the TGM category of the SCC common test sequences with lossy all intra (AI)
random access
and low-delay B configurations
respectively
compared with the latest HEVC SCC at the same encoding and decoding runtimes. The maximum
Y
Bjφntegaard Delta(BD)-rate reduction reaches 2.99% in the AI configuration.
Conclusion
2
The experiment results demonstrate that our algorithm outperforms the DV coding algorithm for IBC in HEVC SCC.
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