Introduction

This column provides a report on the last Video Quality Experts Group (VQEG) plenary meeting, which took place from 26 to 30 June 2023 in San Mateo (USA), hosted by Sony Interactive Entertainment. More than 90 participants worldwide registered for the hybrid meeting, counting with the physical attendance of more than 40 people. This meeting was co-located with the ITU-T SG12 meeting, which took place in the first two days of the week. In addition, more than 50 presentations related to the ongoing projects within VQEG were provided, leading to interesting discussions among the researchers attending the meeting. All the related information, minutes, and files from the meeting are available online on the VQEG meeting website, and video recordings of the meeting are available on Youtube.

In this meeting, there were several aspects that can be relevant for the SIGMM community working on quality assessment. For instance, there are interesting new work items and efforts on updating existing recommendations discussed in the ITU-T SG12 co-located meeting (see the section about the Intersector Rapporteur Group on Audiovisual Quality Assessment). In addition, there was an interesting panel related to deep learning for video coding and video quality with experts from different companies (e.g., Netflix, Adobe, Meta, and Google) (see the Emerging Technologies Group section). Also, a special session on Quality of Experience (QoE) for gaming was organized, involving researchers from several international institutions. Apart from this, readers may be interested in the presentation about MPEG activities on quality assessment and the different developments from industry and academia on tools, algorithms and methods for video quality assessment.

We encourage readers interested in any of the activities going on in the working groups to check their websites and subscribe to the corresponding reflectors, to follow them and get involved.

Overview of VQEG Projects

Audiovisual HD (AVHD)

The AVHD group investigates improved subjective and objective methods for analyzing commonly available video systems. In this meeting, there were several presentations related to topics covered by this group, which were distributed in different sessions during the meeting.

Nabajeet Barman (Kingston University, UK) presented a datasheet for subjective and objective quality assessment datasets. Ali Ak (Nantes Université, France) delivered a presentation on the acceptability and annoyance of video quality in context. Mikołaj Leszczuk (AGH University, Poland) presented a crowdsourcing pixel quality study using non-neutral photos. Kamil Koniuch (AGH University, Poland) discussed about the role of theoretical models in ecologically valid studies, covering the example of a video quality of experience model. Jingwen Zhu (Nantes Université, France) presented her work on evaluating the streaming experience of the viewers with Just Noticeable Difference (JND)-based Encoding. Also, Lucjan Janowski (AGH University, Poland) talked about proposing a more ecologically-valid experiment protocol using YouTube platform.

In addition, there were four presentations by researchers from the industry sector. Hojat Yeganeh (SSIMWAVE/IMAX, USA) talked about how more accurate video quality assessment metrics would lead to more savings. Lukas Krasula (Netflix, USA) delivered a presentation on subjective video quality for 4K HDR-WCG content using a browser-based approach for at-home testing. Also, Christos Bampis (Netflix, USA) presented the work done by Netflix on improving video quality with neural networks. Finally, Pranav Sodhani (Apple, USA) talked about how to evaluate videos with the Advanced Video Quality Tool (AVQT).

Quality Assessment for Health applications (QAH)

The QAH group works on the quality assessment of health applications, considering both subjective evaluation and the development of datasets, objective metrics, and task-based approaches. The group is currently working towards an ITU-T recommendation for the assessment of medical contents. In this sense, Meriem Outtas (INSA Rennes, France) led an editing session of a draft of this recommendation.

Statistical Analysis Methods (SAM)

The SAM group works on improving analysis methods both for the results of subjective experiments and for objective quality models and metrics. The group is currently working on updating and merging the ITU-T recommendations P.913, P.911, and P.910.

Apart from this, several researchers presented their works on related topics. For instance, Pablo Pérez (Nokia XR Lab, Spain) presented (not so) new findings about transmission rating scale and subjective scores. Also, Jingwen Zhu (Nantes Université, France) presented ZREC, an approach for mean and percentile opinion scores recovery. In addition, Andreas Pastor (Nantes Université, France) presented three works: 1) on the accuracy of open video quality metrics for local decision in AV1 video codec, 2) on recovering quality scores in noisy pairwise subjective experiments using negative log-likelihood, and 3) on guidelines for subjective haptic quality assessment, considering a case study on quality assessment of compressed haptic signals. Lucjan Janowski (AGH University, Poland) discussed about experiment precision, proposing experiment precision measures and methods for experiments comparison. Finally, there were three presentations from members of the University of Konstanz (Germany). Dietmar Saupe presented the JPEG AIC-3 activity on fine-grained assessment of subjective quality of compressed images, Mohsen Jenadeleh talked about how relaxed forced choice improves performance of visual quality assessment methods, and Mirko Dulfer presented his work on quantization for Mean Opinion Score (MOS) recovery in Absolute Category Rating (ACR) experiments.

Computer Generated Imagery (CGI)

CGI group is devoted to analyzing and evaluating of computer-generated content, with a focus on gaming in particular. In this meeting, Saman Zadtootaghaj (Sony Interactive Entertainment, Germany) an Nabajeet Barman (Kingston University, UK) organized a special gaming session, in which researchers from several international institutions presented their work in this topic. Among them, Yu-Chih Chen (UT Austin LIVE Lab, USA) presented GAMIVAL, a Video Quality Prediction on Mobile Cloud Gaming Content. Also, Urvashi Pal (Akamai, USA) delivered a presentation on web streaming quality assessment via computer vision applications over cloud. Mathias Wien (RWTH Aachen University, Germany) provided updates on ITU-T P.BBQCG work item, dataset and model development. Avinab Saha (UT Austin LIVE Lab, USA) presented a study of subjective and objective quality assessment of mobile cloud gaming videos. Finally, Irina Cotanis (Infovista, Sweden) and Karan Mitra (Luleå University of Technology, Sweden) presented their work towards QoE models for mobile cloud and virtual reality games.

No Reference Metrics (NORM)

The NORM group is an open collaborative project for developing no-reference metrics for monitoring visual service quality. In this meeting, Margaret Pinson (NTIA, USA) and Ioannis Katsavounidis (Meta, USA), two of the chairs of the group, provided a summary of NORM successes and discussion of current efforts for improved complexity metric. In addition, there were six presentations dealing with related topics. C.-C. Jay Kuo (University of Southern California, USA) talked about blind visual quality assessment for mobile/edge computing. Vignesh V. Menon (University of Klagenfurt, Austria) presented the updates of the Video Quality Analyzer (VQA). Yilin Wang (Google/YouTube, USA) gave a talk on the recent updates on the Universal Video Quality (UVQ). Farhad Pakdaman (Tampere University, Finland) and Li Yu (Nanjing University, China), presented a low complexity no-reference image quality assessment based on multi-scale attention mechanism with natural scene statistics. Finally, Mikołaj Leszczuk (AGH University, Poland) presented his work on visual quality indicators adapted to resolution changes and on considering in-the-wild video content as a special case of user generated content and a system for its recognition.

Emerging Technologies Group (ETG)

The main objective of the ETG group is to address various aspects of multimedia that do not fall under the scope of any of the existing VQEG groups. The topics addressed are not necessarily directly related to “video quality” but can indirectly impact the work addressed as part of VQEG. This group aims to provide a common platform for people to gather together and discuss new emerging topics, discuss possible collaborations in the form of joint survey papers/whitepapers, funding proposals, etc.

One of the topics addressed by this group is related to the use of artificial-intelligence technologies to different domains, such as compression, super-resolution, and video quality assessment. In this sense, Saman Zadtootaghaj (Sony Interactive Entertainment, Germany) organized a panel session with experts from different companies (e.g., Netflix, Adobe, Meta, and Google) on deep learning in the video coding and video quality domains. In this sense, Marcos Conde (Sony Interactive Entertainment, Germany) and David Minnen (Google, USA) gave a talk on generative compression and the challenges for quality assessment.

Another topic covered by this group is greening of streaming and related trends. In this sense, Vignesh V. Menon and Samira Afzal (University of Klagenfurt, Austria) presented their work on green variable framerate encoding for adaptive live streaming. Also, Prajit T. Rajendran (Université Paris Saclay, France) and Vignesh V. Menon (University of Klagenfurt, Austria) delivered a presentation on energy efficient live per-title encoding for adaptive streaming. Finally, Berivan Isik (Stanford University, USA) talked about sandwiched video compression to efficiently extending the reach of standard codecs with neural wrappers.

Joint Effort Group (JEG) – Hybrid

The JEG group was focused on a joint work to develop hybrid perceptual/bitstream metrics and gradually evolved over time to include several areas of Video Quality Assessment (VQA), such as the creation of a large dataset for training such models using full-reference metrics instead of subjective metrics. In addition, the group will include under its activities the VQEG project Implementer’s Guide for Video Quality Metrics (IGVQM).

Apart from this, there were three presentations addressing related topics in this meeting. Nabajeet Barman (Kingston University, UK) presented a subjective dataset for multi-screen video streaming applications. Also, Lohic Fotio (Politecnico di Torino, Italy) presented his works entitled “Human-in-the-loop” training procedure of the artificial-intelligence-based observer (AIO) of a real subject and advances on the “template” on how to report DNN-based video quality metrics.

The website of the group includes a list of activities of interest, freely available publications, and other resources.

Immersive Media Group (IMG)

The IMG group is focused on the research on quality assessment of immersive media. The main joint activity going on within the group is the development of a test plan to evaluate the QoE of immersive interactive communication systems, which is carried out in collaboration with ITU-T through the work item P.IXC. In this meeting, Pablo Pérez (Nokia XR Lab, Spain) and Jesús Gutiérrez (Universidad Politécnica de Madrid, Spain) provided a report on the status of the test plan, including the test proposals from 13 different groups that have joined the activity, which will be launched in September.

In addition to this, Shirin Rafiei (RISE, Sweden) delivered a presentation on her work on human interaction in industrial tele-operated driving through a laboratory investigation.

Quality Assessment for Computer Vision Applications (QACoViA)

The goal of the QACoViA group is to study the visual quality requirements for computer vision methods, where the “final observer” is an algorithm. In this meeting, Avrajyoti Dutta (AGH University, Poland) delivered a presentation dealing with the subjective quality assessment of video summarization algorithms through a crowdsourcing approach.

Intersector Rapporteur Group on Audiovisual Quality Assessment (IRG-AVQA)

This VQEG meeting was co-located with the rapporteur group meeting of ITU-T Study Group 12 – Question 19, coordinated by Chulhee Lee (Yonsei University, Korea). During the first two days of the week, the experts from ITU-T and VQEG worked together on various topics. For instance, there was an editing session to work together on the VQEG proposal to merge the ITU-T Recommendations P.910, P.911, and P.913, including updates with new methods. Another topic addressed during this meeting was the working item “P.obj-recog”, related to the development of an object-recognition-rate-estimation model in surveillance video of autonomous driving. In this sense, a liaison statement was also discussed with the VQEG AVHD group. Also in relation to this group, another liaison statement was discussed on the new work item “P.SMAR” on subjective tests for evaluating the user experience for mobile Augmented Reality (AR) applications.

Other updates

One interesting presentation was given by Mathias Wien (RWTH Aachen University, Germany) on the quality evaluation activities carried out within the MPEG Visual Quality Assessment group, including the expert viewing tests. This presentation and the follow-up discussions will help to strengthen the collaboration between VQEG and MPEG on video quality evaluation activities.

The next VQEG plenary meeting will take place in autumn 2023 and will be announced soon on the VQEG website.

The 143rd MPEG meeting took place in person in Geneva, Switzerland. The official press release can be accessed here and includes the following details:

• MPEG finalizes the Carriage of Uncompressed Video and Images in ISOBMFF
• MPEG reaches the First Milestone for two ISOBMFF Enhancements
• MPEG ratifies Third Editions of VVC and VSEI
• MPEG reaches the First Milestone of AVC (11th Edition) and HEVC Amendment
• MPEG Genomic Coding extended to support Joint Structured Storage and Transport of Sequencing Data, Annotation Data, and Metadata
• MPEG completes Reference Software and Conformance for Geometry-based Point Cloud Compression

We have adjusted the press release to suit the audience of ACM SIGMM and emphasized research on video technologies. This edition of the MPEG column centers around ISOBMFF and video codecs. As always, the column will conclude with an update on MPEG-DASH.

ISOBMFF Enhancements

The ISO Base Media File Format (ISOBMFF) supports the carriage of a wide range of media data such as video, audio, point clouds, haptics, etc., which has now been further extended to uncompressed video and images.

ISO/IEC 23001-17 – Carriage of uncompressed video and images in ISOBMFF – specifies how uncompressed 2D image and video data is carried in files that comply with the ISOBMFF family of standards. This encompasses a range of data types, including monochromatic and colour data, transparency (alpha) information, and depth information. The standard enables the industry to effectively exchange uncompressed video and image data while utilizing all additional information provided by the ISOBMFF, such as timing, color space, and sample aspect ratio for interoperable interpretation and/or display of uncompressed video and image data.

ISO/IEC 14496-15 (based on ISOBMFF) provides the basis for “network abstraction layer (NAL) unit structured video coding formats” such as AVC, HEVC, and VVC. The current version is the 6th edition, which has been amended to support neural-network post-filter supplemental enhancement information (SEI) messages. This amendment defines the carriage of the neural-network post-filter characteristics (NNPFC) SEI messages and the neural-network post-filter activation (NNPFA) SEI messages to enable the delivery of (i) a base post-processing filter and (ii) a series of neural network updates synchronized with the input video pictures/frames.

Research aspects: While the former, the carriage of uncompressed video and images in ISOBMFF, seems to be something obvious to be supported within a file format, the latter enables to use neural network-based post-processing filters to enhance video quality after the decoding process, which is an active field of research. The current extensions with the file format provide a baseline for the evaluation (cf. also next section).

Video Codec Enhancements

MPEG finalized the specifications of the third editions of the Versatile Video Coding (VVC, ISO/IEC 23090-3) and the Versatile Supplemental Enhancement Information (VSEI, ISO/IEC 23002-7) standards. Additionally, MPEG issued the Committee Draft (CD) text of the eleventh edition of the Advanced Video Coding (AVC, ISO/IEC 14496-10) standard and the Committee Draft Amendment (CDAM) text on top of the High Efficiency Video Coding standard (HEVC, ISO/IEC 23008-2).

These SEI messages include two systems-related SEI messages, (a) one for signaling of green metadata as specified in ISO/IEC 23001-11 and (b) the other for signaling of an alternative video decoding interface for immersive media as specified in ISO/IEC 23090-13. Furthermore, the neural network post-filter characteristics SEI message and the neural-network post-processing filter activation SEI message have been added to AVC, HEVC, and VVC.

The two SEI messages for describing and activating post-filters using neural network technology in video bitstreams could, for example, be used for reducing coding noise, spatial and temporal upsampling (i.e., super-resolution and frame interpolation), color improvement, or general denoising of the decoder output. The description of the neural network architecture itself is based on MPEG’s neural network representation standard (ISO/IEC 15938 17). As results from an exploration experiment have shown, neural network-based post-filters can deliver better results than conventional filtering methods. Processes for invoking these new post-filters have already been tested in a software framework and will be made available in an upcoming version of the VVC reference software (ISO/IEC 23090-16).

Research aspects: SEI messages for neural network post-filters (NNPF) for AVC, HEVC, and VVC, including systems supports within the ISOBMFF, is a powerful tool(box) for interoperable visual quality enhancements at the client. This tool(box) will (i) allow for Quality of Experience (QoE) assessments and (ii) enable the analysis thereof across codecs once integrated within the corresponding reference software.

MPEG-DASH Updates

The current status of MPEG-DASH is depicted in the figure below:

The latest edition of MPEG-DASH is the 5th edition (ISO/IEC 23009-1:2022) which is publicly/freely available here. There are currently three amendments under development:

• ISO/IEC 23009-1:2022 Amendment 1: Preroll, nonlinear playback, and other extensions. This amendment has been ratified already and is currently being integrated into the 5th edition of part 1 of the MPEG-DASH specification.
• ISO/IEC 23009-1:2022 Amendment 2: EDRAP streaming and other extensions. EDRAP stands for Extended Dependent Random Access Point and at this meeting the Draft Amendment (DAM) has been approved. EDRAP increases the coding efficiency for random access and has been adopted within VVC.
• ISO/IEC 23009-1:2022 Amendment 3: Segment sequences for random access and switching. This amendment is at Committee Draft Amendment (CDAM) stage, the first milestone of the formal standardization process. This amendment aims at improving tune-in time for low latency streaming.

Additionally, MPEG Technologies under Consideration (TuC) comprises a few new work items, such as content selection and adaptation logic based on device orientation and signalling of haptics data within DASH.

Finally, part 9 of MPEG-DASH — redundant encoding and packaging for segmented live media (REAP) — has been promoted to Draft International Standard (DIS). It is expected to be finalized in the upcoming meetings.

Research aspects: Random access has been extensively evaluated in the context of video coding but not (low latency) streaming. Additionally, the TuC item related to content selection and adaptation logic based on device orientation raises QoE issues to be further explored.

The 144th MPEG meeting will be held in Hannover from October 16-20, 2023. Click here for more information about MPEG meetings and their developments.

JPEG Trust on a mission to re-establish trust in digital media

The 99th JPEG meeting was held online, from 24th to 28th April 2023.

Providing tools suitable for establishing provenance, authenticity and ownership of multimedia content is one of the most difficult challenges faced nowadays, considering the technological models that allow effective multimedia data manipulation and generation. As in the past, the JPEG Committee is again answering the emerging challenges in multimedia. JPEG Trust is a standard offering solutions to media authenticity, provenance and ownership.

Furthermore, learning-based coding standards, JPEG AI and JPEG Pleno Learning-based Point Cloud Coding, continue their development. New verification models that incorporate the technological developments resulting from verification experiments and contributions have been approved.

Also relevant, the responses to the Calls for Contributions on standardization of quality models of JPEG AIC and JPEG Pleno Light Field Quality Assessment received responses and started a collaborative process to define new standards.

The 99^th JPEG meeting had the following highlights:

• New JPEG Trust international standard targets media authenticity
• JPEG AI new verification model
• JPEG DNA releases its call for proposals
• JPEG Pleno Light Field Quality Assessment analyses the response to the call for contributions
• JPEG AIC analyses the response to the call for contributions
• JPEG XE identifies use cases and requirements for event based vision
• JPEG Systems: JUMBF second edition is progressing to publication stage
• JPEG NFT prepares a call for proposals
• JPEG XS progress for its third edition

The following summarizes the major achievements during the 99th JPEG meeting.

New JPEG Trust international standard targets media authenticity

Drawing reliable conclusions about the authenticity of digital media is complicated, and becoming more so as AI-based synthetic media such as Deep Fakes and Generative Adversarial Netwodrks (GANs) start appearing. Consumers of social media are challenged to assess the trustworthiness of the media they encounter, and agencies that depend on the authenticity of media assets must be concerned with mistaking fake media for real, with risks of real-world consequences.

To address this problem and to provide leadership in global interoperable media asset authenticity, JPEG initiated development of a new international standard: JPEG Trust. JPEG Trust defines a framework for establishing trust in media. This framework adresses aspects of authenticity, provenance and integrity through secure and reliable annotation of media assets throughout their life cycle. The first part, “Core foundation”, defines the JPEG Trust framework and provides building blocks for more elaborate use cases. It is expected that the standard will evolve over time and be extended with additional specifications.

JPEG Trust arises from a four-year exploration of requirements for addressing mis- and dis-information in online media, followed by a 2022 Call for Proposals, conducted by international experts from industry and academia from all over the world.

The new standard is expected to be published in 2024. To stay updated on JPEG Trust, please regularly check the JPEG website for the latest information.

JPEG AI

The JPEG AI activity progressed at this meeting with more than 60 technical contributions submitted for improvements and additions to the Verification Model (VM), which after some discussion and analysis, resulted in several adoptions for integration into the future VM3.0. These adoptions target the speed-up of the decoding process, namely the replacement of the range coder by an asymmetric numeral system, support for multi-threading or/and single instruction multiple data operations, and parallel decoding with sub-streams. The JPEG AI context module was significantly accelerated with a new network architecture along with other synthesis transform and entropy decoding network simplifications. Moreover, a lightweight model was also adopted targeting mobile devices, providing 10%-15% compression efficiency gains over VVC Intra at just 20-30 kMAC/pxl. In this context, JPEG AI will start the development and evaluation of two JPEG AI VM configurations at two different operating points: lightweight and high.

At the 99th meeting, the JPEG AI requirements were reviewed and it was concluded that most of the key requirements will be achieved by the previously anticipated timeline for DIS (scheduled for Oct. 2023) and thus version 1 of the JPEG AI standard will go as planned without changes in its timeline and with a clear focus on image reconstruction. Some core requirements, such as those addressing computer vision and image processing tasks as well as progressive decoding, will be addressed in a version 2 along with other tools that further improve requirements already addressed in version 1, such as better compression efficiency.

JPEG Pleno Learning-based Point Cloud coding

The JPEG Pleno Point Cloud activity progressed at this meeting with a major improvement to its VM providing improved performance and control over the balance between the coding of geometry and colour via a split geometry and colour coding framework. Colour attribute information is encoded using JPEG AI resulting in enhanced performance and compatibility with the ecosystem of emerging high-performance JPEG codecs. Prior to the 100th JPEG Meeting, JPEG experts will investigate possible advancements to the VM in the areas of attention models, sparse tensor convolution, and support for residual lossless coding.

JPEG DNA

The JPEG Committee has been working on an exploration for coding of images in quaternary representations particularly suitable for image archival on DNA storage. The scope of JPEG DNA is the creation of a standard for efficient coding of images that considers biochemical constraints and offers robustness to noise introduced by the different stages of the storage process that is based on DNA synthetic polymers. During the 99th JPEG meeting, a final call for proposals for JPEG DNA was issued and made public, as a first concrete step towards standardization.

The final call for proposals for JPEG DNA is complemented by a JPEG DNA Common Test Conditions document which is also made public, describing details about the dataset, operating points, anchors and performance assessment methodologies and metrics that will be used to evaluate anchors and future proposals to be submitted. A set of exploration studies has validated the procedures outlined in the final call for proposals for JPEG DNA. The deadline for submission of proposals to the Call for Proposals for JPEG DNA is 2 October 2023, with a pre-registration due by 10 July 2023. The JPEG DNA international standard is expected to be published by early 2025.

JPEG Pleno Light Field Quality Assessment

At the 99th JPEG meeting two contributions were received in response to the JPEG Pleno Final Call for Contributions (CfC) on Subjective Light Field Quality Assessment.

• Contribution 1: presents a 3-step subjective quality assessment framework, with a pre-processing step; a scoring step; and a data processing step. The contribution includes a software implementation of the quality assessment framework.
• Contribution 2: presents a multi-view light field dataset, comprising synthetic light fields. It provides RGB + ground-truth depth data, realistic and challenging blender scenes, with various textures, fine structures, rich depth, specularities, non-Lambertian areas, and difficult materials (water, patterns, etc).

The received contributions will be considered in the development of a modular framework based on a collaborative process addressing the use cases and requirements under the JPEG Pleno Quality Assessment of light fields standardization effort.

JPEG AIC

Three contributions in response to the JPEG Call for Contributions (CfC) on Subjective Image Quality Assessment were received at the 99th JPEG meeting. One contribution presented a new subjective quality assessment methodology that combines relative and absolute data. The second contribution reported a new subjective quality assessment methodology based on triplet comparison with boosting techniques. Finally, the last contribution reported a new pairwise sampling methodology.

These contributions will be considered in the development of the standard, following a collaborative process. Several core experiments were designed to assist the creation of a Working Draft (WD) for the future JPEG AIC Part 3 standard.

JPEG XE

The JPEG committee continued with the exploration activity on Event-based Vision, called JPEG XE. Event-based Vision revolves around a new and emerging image modality created by event-based visual sensors. At this meeting, the scope was defined to be the creation and development of a standard to represent events in an efficient way allowing interoperability between sensing, storage, and processing, targeting machine vision applications. Events in the context of this standard are defined as the messages that signal the result of an observation at a precise point in time, typically triggered by a detected change in the physical world. The exploration activity is currently working on the definition of the use cases and requirements.

An Ad-hoc Group has been established. To stay informed about the activities please join the event based imaging Ad-hoc Group mailing list.

JPEG XL

The second editions of JPEG XL Part 1 (Core coding system) and Part 2 (File format) have proceeded to the DIS stage. These second editions provide clarifications, corrections and editorial improvements that will facilitate independent implementations. Experiments are planned to prepare for a second edition of JPEG XL Part 3 (Conformance testing), including conformance testing of the independent implementations J40, jxlatte, and jxl-oxide.

JPEG Systems

The second edition of JUMBF (JPEG Universal Metadata Box Format, ISO/IEC 19566-5) is progressing to the IS publication stage; the second edition brings new capabilities and support for additional types of media.

JPEG NFT

Many Non-Fungible Tokens (NFTs) point to assets represented in JPEG formats or can be represented in current and emerging formats under development by the JPEG Committee. However, various trust and security concerns have been raised about NFTs and the digital assets on which they rely. To better understand user requirements for media formats, the JPEG Committee conducted an exploration on NFTs. The scope of JPEG NFT is the creation of effective specifications that support a wide range of applications relying on NFTs applied to media assets. The standard will be secure, trustworthy and eco-friendly, allowing for an interoperable ecosystem relying on NFT within a single application or across applications. As a result of the exploration, at the 99th JPEG Meeting the committee released a “Draft Call for Proposals on JPEG NFT” and associated updated “Use Cases and Requirements for JPEG NFT”. Both documents are made publicly available for review and feedback.

JPEG XS

The JPEG committee continued its work on the JPEG XS 3rd edition. The primary goal of the 3rd edition is to deliver the same image quality as the 2nd edition, but with half of the required bandwidth. For Part 1 – Core coding tools – the Draft International Standard will proceed to ISO/IEC ballot. This is a significant step in the standardization process with all the core coding technology now final. Most notably, Part 1 adds a temporal decorrelation coding mode to further improve the coding efficiency, while keeping the low-latency and low-complexity core aspects of JPEG XS. Furthermore, Part 2 – Profiles and buffer models – and Part 3 – Transport and container formats – will proceed to Committee Draft consultation. Part 2 is important as it defines the conformance points for JPEG XS compliance. Completion of the JPEG XS 3rd edition standard is scheduled for January 2024.

Final Quote

“The creation of standardized tools to bring assurance of authenticity, provenance and ownership for multimedia content is the most efficient path to suppress the abusive use of fake media. JPEG Trust will be the first international standard that provides such tools.” said Prof. Touradj Ebrahimi, the Convenor of the JPEG Committee.

Future JPEG meetings are planned as follows:

• No 100, will be in Covilhã, Portugal from 17-21 July 2023
• No 101, will be online from 30 October – 3 November 2023

A zip package containing the official JPEG logo and logos of all JPEG standards can be downloaded here.