JPEG格式
计算机科学
标准化
JPEG 2000
人工智能
图像压缩
图像处理
编码(社会科学)
计算机视觉
数据压缩
操作系统
图像(数学)
统计
数学
作者
João Ascenso,Elena Alshina,Touradj Ebrahimi
出处
期刊:IEEE MultiMedia
[IEEE Computer Society]
日期:2023-01-01
卷期号:30 (1): 100-111
被引量:97
标识
DOI:10.1109/mmul.2023.3245919
摘要
The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Telecommunication Union - Telecommunication Sector (ITU-T) for the development of the first image coding standard based on machine learning (a subset of artificial intelligence), offering a single stream, compact compressed domain representation, targeting both human visualization and machine consumption. The main motivation for this upcoming standard is the excellent performance of tools based on deep neural networks, in image coding, computer vision, and image processing tasks. The JPEG AI aims to develop an image coding standard addressing the needs of a wide range of applications such as cloud storage, visual surveillance, autonomous vehicles and devices, image collection storage and management, live monitoring of visual data, and media distribution. This article presents and discusses the rationale behind the JPEG AI vision, notably how this new standardization initiative aims to shape the future of image coding, through relevant application-driven use cases. The JPEG AI requirements, the JPEG AI history, and current status are also presented, offering a glimpse of the development of the first learning-based image coding standard.
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