FPGA-based implementation of the VVC low-frequency non-separable transform

IF 2.9 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Real-Time Image Processing Pub Date : 2024-05-18 DOI:10.1007/s11554-024-01471-3
Fatma Belghith, Sonda Ben Jdidia, Bouthaina Abdallah, Nouri Masmoudi
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Abstract

The Versatile Video Coding (VVC) standard, released in July 2020, brings better coding performance than the High-Efficiency Video Coding (HEVC) thanks to the introduction of new coding tools. The transform module in the VVC standard incorporates the Multiple Transform Selection (MTS) concept, which relies on separable Discrete Cosine Transform (DCT)/Discrete Sine Transform (DST) kernels, and the recently introduced Low-Frequency Non-Separable Transform (LFNST). This latter serves as a secondary transform process, enhancing coding efficiency by further decorrelating residual samples. However, it introduces heightened computational complexity and substantial resource allocation demands, potentially complicating its hardware implementation. This paper introduces an effective and cost-efficient hardware architecture for LFNST. The proposed design employs additions and bit-shifting operations preserving hardware logic usage. The synthesis results for an Arria 10 10AX115N1F45E1SG FPGA device demonstrate that the logic cost is only of 26% of the available hardware resources. Additionally, the proposed design is working at 204 MHz and can process Ultra High Definition (UHD) 4K videos at up to 60 frames per second (fps).

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基于 FPGA 的 VVC 低频非分离变换实现方案
由于引入了新的编码工具,2020 年 7 月发布的通用视频编码(VVC)标准带来了比高效视频编码(HEVC)更好的编码性能。VVC 标准中的变换模块采用了多重变换选择(MTS)概念,它依赖于可分离的离散余弦变换(DCT)/离散正弦变换(DST)核,以及最近推出的低频非分离变换(LFNST)。后者是一种二次变换过程,通过进一步对残余样本进行去相关处理来提高编码效率。然而,LFNST 带来了更高的计算复杂性和大量的资源分配需求,可能会使其硬件实施变得复杂。本文为 LFNST 引入了一种高效、低成本的硬件架构。拟议的设计采用了加法和位移操作,保留了硬件逻辑的使用。Arria 10 10AX115N1F45E1SG FPGA 器件的综合结果表明,逻辑成本仅占可用硬件资源的 26%。此外,拟议设计的工作频率为 204 MHz,能以高达每秒 60 帧(fps)的速度处理超高清(UHD)4K 视频。
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来源期刊
Journal of Real-Time Image Processing
Journal of Real-Time Image Processing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
6.80
自引率
6.70%
发文量
68
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.
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