End-to-End Distortion Modeling for Error-Resilient Screen Content Video Coding

被引:6
作者
Tang, Tong [1 ,2 ,3 ]
Yin, Zhiyang [1 ,2 ,3 ]
Li, Jie [1 ,2 ,3 ]
Wang, Honggang [4 ]
Wu, Dapeng [1 ,2 ,3 ]
Wang, Ruyan [1 ,2 ,3 ]
机构
[1] Chongqing Univ Posts & Telecommun, Sch Commun & Informat Engn, Chongqing 400065, Peoples R China
[2] Adv Network & Intelligent Interconnect Technol Key, Chongqing 400065, Peoples R China
[3] Chongqing Key Lab Ubiquitous Sensing & Networking, Chongqing 400065, Peoples R China
[4] Univ Massachusetts Dartmouth, Elect & Comp Engn Dept, N Dartmouth, MA 02747 USA
基金
中国国家自然科学基金;
关键词
Distortion; Encoding; Streaming media; Decoding; Image coding; Video coding; Estimation; Screen content video; error resilient coding; distortion modeling; error concealment; OPTIMIZATION; ALLOCATION; QUALITY; HEVC;
D O I
10.1109/TMM.2023.3323895
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To improve the compression performance of screen content coding, extension coding standards (HEVC-SCC, VVC-SCC) have been developed. However, considering the compression ratio alone may lead to packet losses in bitstreams which may cause plenty of images decoded incorrectly, degrading the video quality at the receiver side. Thus, it urgently needs to study source-channel jointly coding scheme of screen content video. The most significant challenge lies in the complex spatial-temporal characteristics of screen content video, which complicate the creation of an accurate end-to-end distortion model. In this article, we delve into the traits of screen content video and construct an end-to-end distortion model. Building upon this, we introduce an error resilient coding scheme specifically for screen content video. More specifically, we first consider the characteristic of non-stationary temporal domain variation and classify the screen content images into three types of frames using a fast block-searching method. We then propose an adaptive error concealment method, taking into account the spatial-temporal prediction characteristics. Following this, we derive a pixel-level end-to-end distortion model and incorporate it into the rate distortion optimization process. Our experimental results reveal that, compared to state-of-the-art methods, our proposed method significantly enhances both objective and subjective quality across a variety of channel conditions.
引用
收藏
页码:4458 / 4468
页数:11
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