ISO/IEC 6048-1:2025
(Main)Information technology — JPEG AI learning-based image coding system — Part 1: Core coding system
Information technology — JPEG AI learning-based image coding system — Part 1: Core coding system
This document specifies an image coding technology known as JPEG AI learning-based image coding (JPEG AI) comprising an image coding technology that facilitates the compression and processing of images for both human and machine vision. The scope of the JPEG AI document is the creation of a learning-based image coding standard offering a single-stream, compact compressed domain representation, targeting both human visualization, with significant compression efficiency improvement over image coding standards in common use at equivalent subjective quality, and effective performance for image processing and computer vision tasks. The core coding system describes JPEG AI standard for the human vision reconstruction task and thus specifies the JPEG AI specifies the parsing coded stream and the image reconstruction process. Only the syntax format, semantics, and associated decoding process requirements are specified, while other matters such as pre-processing, the encoding process, system signalling and multiplexing, data loss recovery, post-processing, and video display are considered to be outside the scope of this document. This document is designed to be generic in the sense that it serves a wide range of applications, bit rates, resolutions, qualities and services. In the course of creating this document, several requirements from typical applications have been considered, necessary algorithmic elements have been developed, and these have been integrated into a single syntax. Hence, this document is designed to facilitate image data interchange among different applications and services.
Titre manque — Partie 1: Titre manque
General Information
Standards Content (Sample)
International
Standard
ISO/IEC 6048-1
First edition
Information technology — JPEG
2025-09
AI learning-based image coding
system —
Part 1:
Core coding system
Reference number
© ISO/IEC 2025
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ii
Foreword
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participate in the development of International Standards through technical committees established by the
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represent the latest information, which may be obtained from the patent database available at www.iso.org/patents
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www.iec.ch/understanding-standards.
This document was prepared by ITU-T (as ITU-T T.840.1) and drafted in accordance with its editorial
rules, in collaboration with Joint Technical Committee ISO/IEC JTC 1, Information technology, Subcommittee
SC 29, Coding of audio, picture, multimedia and hypermedia information.
A list of all parts in the ISO/IEC 6048 series can be found on the ISO and IEC websites.
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© ISO/IEC 2025 – All rights reserved
iii
INTERNATIONAL STANDARD ISO/IEC 6048-1
RECOMMENDATION ITU-T T.840.1
Information technology – JPEG AI learning-based image coding system: Core coding system
Summary
Recommendation ITU-T T.840.1 | ISO/IEC 6048-1 specifies an image coding technology known as JPEG AI learning-
based image coding (JPEG AI) and it has been designed with multi-task goal. It facilitates the compression and processing
of images for both human and machine vision. This Recommendation | International Standard describes the JPEG AI
learning-based standard for the creation of an image from the parsed single-stream, which contains the compact compressed
domain representation, targeting both human visualization, with significant compression efficiency improvement over
image coding standards in common use at equivalent subjective quality, and effective performance for image processing
and computer vision tasks.
Core coding system describes the JPEG AI standard for the human vision reconstruction task and thus specifies the parsing
of the coded stream and the image reconstruction process.
The trainable model parameters, which are an integral part of this Recommendation | International Standard, are not
contained in the Specification due to their size. Instead, the trained model parameters are available at:
https://standards.iso.org/iso-iec/6048/-1/ed-1/en/ and https://www.itu.int/myworkspace/#/t-signals/vectors?val=40 (see
subclause 18.2).
This Recommendation | International Standard was developed collaboratively with ISO/IEC JTC 1/SC 29, and corresponds
with ISO/IEC 6048-1 as common text.
*
History
Edition Recommendation Approval Study Group Unique ID
1.0 ITU-T T.840.1 2025-03-16 21 11.1002/1000/16265
Keywords
Coding, compression, decoding, human vision, image, machine vision, neural network.
_______________
*
To access the Recommendation, type the URL https://handle.itu.int/ in the address field of your web
browser, followed by the Recommendation's unique ID.
Rec. ITU-T T.840.1 (03/2025)
© ISO/IEC 2025 – All rights reserved
v
FOREWORD
The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of
telecommunications, and information and communication technologies (ICTs). The ITU Telecommunication
Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical,
operating and tariff questions and issuing Recommendations on them with a view to standardizing
telecommunications on a worldwide basis.
The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes
the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
In some areas of information technology which fall within ITU-T's purview, the necessary standards are
prepared on a collaborative basis with ISO and IEC.
NOTE
In this Recommendation, the expression "Administration" is used for conciseness to indicate both a
telecommunication administration and a recognized operating agency.
Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain
mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the
Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other
obligatory language such as "must" and the negative equivalents are used to express requirements. The use of
such words does not suggest that compliance with the Recommendation is required of any party.
INTELLECTUAL PROPERTY RIGHTS
ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve
the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or
applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of
the Recommendation development process.
As of the date of approval of this Recommendation, ITU had received notice of intellectual property, protected
by patents/software copyrights, which may be required to implement this Recommendation. However,
implementers are cautioned that this may not represent the latest information and are therefore strongly urged
to consult the appropriate ITU-T databases available via the ITU-T website at https://www.itu.int/ITU-T/ipr/.
ITU 2025
All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior
written permission of ITU.
Rec. ITU-T T.840.1 (03/2025)
© ISO/IEC 2025 – All rights reserved
vi
CONTENTS
Page
1 Scope . 1
2 Normative references . 1
2.1 Identical Recommendations | International Standards . 1
2.2 Paired Recommendations | International Standards equivalent in technical content . 1
2.3 Additional references . 1
3 Definitions . 1
4 Abbreviations . 3
5 Conventions . 4
5.1 General . 4
5.2 Arithmetic operators . 4
5.3 Logical operators . 5
5.4 Relational operators . 5
5.5 Bit-wise operators . 5
5.6 Assignment operators . 5
5.7 Range notation . 6
5.8 Mathematical functions . 6
5.9 Order of operation precedence . 6
5.10 Variables, syntax elements and tables . 7
5.11 Text description of logical operations . 8
5.12 Processes . 9
6 Image representation, tensor operations and neural network . 9
6.1 Image representation . 9
6.2 Tensor operations and neural network design elements . 9
6.2.1 Average pooling 8 . 9
6.2.2 Batch normalization . 9
6.2.3 Bicubic upsampling . 10
6.2.4 Concatenation of two tensors . 10
6.2.5 Concatenation of three tensors . 10
6.2.6 Convolution layer . 10
6.2.7 Convolution-based attention block . 10
6.2.8 Cropping layer. 11
6.2.9 Deinteger function . 11
6.2.10 Downsampling layer . 11
6.2.11 Downshuffle operation . 11
6.2.12 Grouped convolution layer . 12
6.2.13 Layer normalization . 12
6.2.14 Latent combine block . 12
6.2.15 Lightweight residual block . 13
6.2.16 Matrix transpose . 13
6.2.17 Matrix multiplication . 13
6.2.18 Multiplication of tensors by a constant . 13
6.2.19 Nearest neighbour downsampling . 13
6.2.20 Padding layer . 14
6.2.21 Per element absolute value .
...
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