Hardware-friendly fast rate-distortion optimization algorithm for AV1 encoder

IF 2.9 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Real-Time Image Processing Pub Date : 2024-08-27 DOI:10.1007/s11554-024-01535-4

Ran Tang, Xiaofeng Huang, Yan Cui, Xinnan Guo, Yang Zhou, Haibing Yin, Chenggang Yan

{"title":"Hardware-friendly fast rate-distortion optimization algorithm for AV1 encoder","authors":"Ran Tang, Xiaofeng Huang, Yan Cui, Xinnan Guo, Yang Zhou, Haibing Yin, Chenggang Yan","doi":"10.1007/s11554-024-01535-4","DOIUrl":null,"url":null,"abstract":"<p>The rate distortion optimization (RDO) process aims at achieving optimal coding performance by determining the optimal coding mode according to a certain strategy in the AV1 video coding. However, the high computational complexity and strong data dependency in RDO impede real-time applications. To address these issues, a fast RDO algorithm suitable for hardware implementation is proposed. Firstly, we propose a high-frequency coefficients zero-setting approach to optimize the hardware memory occupation. Then, in the rate-distortion calculation stage, an efficient rate estimation method is proposed based on a statistical feature for the number of quantization coefficients, and the distortion estimation method is proposed by considering intrinsic features in the all-zero block. Finally, a reconstruction approximate model is proposed to solve the low parallelism issue caused by the coupling of pixel reconstruction and prediction data. Experimental results show that the proposed algorithm achieves 68.49% and 50.77% time-saving by 2.73% and 2.95% Bjøntegaard delta rate (BD-Rate) increase on average under all intra (AI) and random access (RA) configurations, respectively.</p>","PeriodicalId":51224,"journal":{"name":"Journal of Real-Time Image Processing","volume":"4 1","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Real-Time Image Processing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s11554-024-01535-4","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}

引用次数: 0

Abstract

The rate distortion optimization (RDO) process aims at achieving optimal coding performance by determining the optimal coding mode according to a certain strategy in the AV1 video coding. However, the high computational complexity and strong data dependency in RDO impede real-time applications. To address these issues, a fast RDO algorithm suitable for hardware implementation is proposed. Firstly, we propose a high-frequency coefficients zero-setting approach to optimize the hardware memory occupation. Then, in the rate-distortion calculation stage, an efficient rate estimation method is proposed based on a statistical feature for the number of quantization coefficients, and the distortion estimation method is proposed by considering intrinsic features in the all-zero block. Finally, a reconstruction approximate model is proposed to solve the low parallelism issue caused by the coupling of pixel reconstruction and prediction data. Experimental results show that the proposed algorithm achieves 68.49% and 50.77% time-saving by 2.73% and 2.95% Bjøntegaard delta rate (BD-Rate) increase on average under all intra (AI) and random access (RA) configurations, respectively.

Abstract Image

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

针对 AV1 编码器的硬件友好型快速速率失真优化算法

速率失真优化（RDO）过程旨在根据 AV1 视频编码中的特定策略确定最佳编码模式，从而实现最佳编码性能。然而，RDO 的高计算复杂性和强数据依赖性阻碍了实时应用。为了解决这些问题，我们提出了一种适合硬件实现的快速 RDO 算法。首先，我们提出了一种高频系数置零方法，以优化硬件内存占用。然后，在速率-失真计算阶段，基于量化系数数的统计特征提出了一种高效的速率估计方法，并通过考虑全零块的内在特征提出了失真估计方法。最后，提出了一种重构近似模型，以解决像素重构和预测数据耦合导致的低并行性问题。实验结果表明，在所有内部（AI）和随机存取（RA）配置下，所提算法分别平均节省了 68.49% 和 50.77% 的时间，比约恩特加尔德三角率（BD-Rate）分别提高了 2.73% 和 2.95%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Journal of Real-Time Image Processing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-ENGINEERING, ELECTRICAL & ELECTRONIC

CiteScore

6.80

自引率

6.70%

发文量

审稿时长

6 months

期刊介绍： Due to rapid advancements in integrated circuit technology, the rich theoretical results that have been developed by the image and video processing research community are now being increasingly applied in practical systems to solve real-world image and video processing problems. Such systems involve constraints placed not only on their size, cost, and power consumption, but also on the timeliness of the image data processed. Examples of such systems are mobile phones, digital still/video/cell-phone cameras, portable media players, personal digital assistants, high-definition television, video surveillance systems, industrial visual inspection systems, medical imaging devices, vision-guided autonomous robots, spectral imaging systems, and many other real-time embedded systems. In these real-time systems, strict timing requirements demand that results are available within a certain interval of time as imposed by the application. It is often the case that an image processing algorithm is developed and proven theoretically sound, presumably with a specific application in mind, but its practical applications and the detailed steps, methodology, and trade-off analysis required to achieve its real-time performance are not fully explored, leaving these critical and usually non-trivial issues for those wishing to employ the algorithm in a real-time system. The Journal of Real-Time Image Processing is intended to bridge the gap between the theory and practice of image processing, serving the greater community of researchers, practicing engineers, and industrial professionals who deal with designing, implementing or utilizing image processing systems which must satisfy real-time design constraints.