Category Archives: Event Report

Abstract

This column introduces the now completed ITU-T P.1204 video quality model standards for assessing sequences up to UHD/4K resolution. Initially developed over two years by ITU-T Study Group 12 (Question Q14/12) and VQEG, the work used a large dataset of 26 subjective tests (13 for training, 13 for validation), each involving at least 24 participants rating sequences on the 5-point ACR scale. The tests covered diverse encoding settings, bitrates, resolutions, and framerates for H.264/AVC, H.265/HEVC, and VP9 codecs. The resulting 5,000-sequence dataset forms the largest lab-based source for model development to date. Initially standardized were P.1204.3, a no-reference bitstream-based model with full bitstream access, P.1204.4, a pixel-based, reduced-/full-reference model, and P.1204.5, a no-reference hybrid model. The current record focuses on the latest additions to the series, namely P.1204.1, a parametric, metadata-based model using only information about which codec was used, plus bitrate, framerate and resolution, and P.1204.2, which in addition uses frame-size and frame-type information to include video-content aspects into the predictions.

Introduction

Video quality under specific encoding settings is central to applications such as VoD, live streaming, and audiovisual communication. In HTTP-based adaptive streaming (HAS) services, bitrate ladders define video representations across resolutions and bitrates, balancing screen resolution and network capacity. Video quality, a key contributor to users’ Quality of Experience (QoE), can vary with bandwidth fluctuations, buffer delays, or playback stalls. 

While such quality fluctuations and broader QoE aspects are discussed elsewhere, this record focuses on short-term video quality as modeled by ITU-T P.1204 for HAS-type content. These models assess segments of around 10s under reliable transport (e.g., TCP, QUIC), covering resolution, framerate, and encoding effects, but excluding pixel-level impairments from packet loss under unreliable transport.

Because video quality is perceptual, subjective tests, laboratory or crowdsourced, remain essential, especially at high resolutions such as 4K UHD under controlled viewing conditions (1.5H or 1.6H viewing distance). Yet, studies show limited perceptual gain between HD and 4K, depending on source content, underlining the need for representative test materials. Given the high cost of such tests, objective (instrumental) models are required for scalable, automated assessment supporting applications like bitrate ladder design and service monitoring.

Four main model classes exist: metadata-based, bitstream-based, pixel-based, and hybrid. Metadata-based models use codec parameters (e.g., resolution, bitrate) and are lightweight; bitstream-based models analyze encoded streams without decoding, as in ITU-T P.1203 and P.1204.3 [1][2][3][7]. Pixel-based models compare decoded frames and include Full Reference and Reduced Reference models (e.g., P.1204.4, and also PSNR [9], SSIM [10], VMAF [11][12]), as well as No Reference variants. Finally, hybrid models combine pixel and bitstream or metadata inputs, exemplified by the ITU-T P.1204.5 standard. These three standards, P.1204.3 P.1204.4 and P.1204.5, formed the initial P.1204 Recommendation series finalized in 2020.

ITU-T P.1204 series completed with P.1204.1 and P.1204.2

The respective standardization project under the Work Item name P.NATS Phase 2 (read: Peanuts) was a unique video quality model development competition conducted in collaboration between ITU-T Study Group 12 (SG12) and the Video Quality Experts Group (VQEG). The target use cases were for up to UHD/4K resolution, with presentation on UHD/4K resolution PC/TV or Mobile/Tablet (MO/TA). For the first time, bitstream-, pixel-based, and hybrid models were jointly developed, trained, and validated, using a large common subjective dataset comprising 26 tests, each with at least 24 participants (see, e.g., [1] for details). The P.NATS Phase 2 work built on the earlier “P.NATS Phase 1” project, which resulted in the ITU-T Rec. P.1203 standards series (P.1203, P.1203.1, P.1203.2, P.1203.3). In the P.NATS Phase 2 project, video quality models in five different categories were evaluated, and different candidates were found to be eligible to be recommended as standards. The initially standardized three models out of the five categories were the aforementioned P.1204.3, P.1204.4 and P.1204.5. However, due to the lack of consensus between the winning proponents, no models were recommended as standards for the category “bitstream Mode 0” with access to high-level metadata only, such as the video codec, resolution, framerate and bitrate used,  and “bitstream Mode 1”, with further access to frame-size information that can be used for content-complexity estimation.

For the latest model additions of P.1204.1 and P.1204.2, subsets of the databases initially used in the P.NATS Phase 2 project were employed for model training. Two different datasets belonging to the two contexts PC/TV and MO/TA were used for training the models. AVT-PNATS-UHD-1 is the dataset for the PC/TV use case and ERCS-PNATS-UHD-1 the dataset used for the MO/TA use case. 

AVT-PNATS-UHD-1 [7] consists of four different subjective tests conducted by TU Ilmenau as part of the P.NATS Phase 2 competition. The target resolution of these datasets was 3840 x 2160 pixels. ERCS-PNATS-UHD-1 [1] is a dataset targeting the MO/TA use case. It consists of one subjective test conducted by Ericsson as part of the P.NATS Phase 2 competition. The target resolution of these datasets was 2560 x 1440 pixels. 

For model performance evaluation, beyond AVT-PNATS-UHD-1, further externally available video-quality test databases were used, as outlined in the following.

AVT-VQDB-UHD-1: This is a publicly available dataset and consists of four different subjective tests. All the four tests had a full-factorial design. In total, 17 different SRCs with a duration of 7-10 s were used across all the four tests. All the sources had a resolution of 3840×2160 pixels and a framerate of 60 fps. For HRC design, bitrate was selected in fixed (i.e. non-adaptive) values per PVS between 200kbps and 40000kbps, resolution between 360p and 2160p and framerate between 15fps and 60fps. In all the tests, a 2-pass encoding approach was used to encode the videos, with medium preset for H.264 and H.265, and the speed parameter for VP9 set to the default value “0”. A total of 104 participants in the four tests.

GVS: This dataset consists of 24 SRCs that have been extracted from 12 different games. The SRCs are of 1920×1080 pixel resolution, 30fps framerate and have a duration of 30s . The HRC design included three different resolutions, namely, 480p, 720p and 1080p . 90 PVSs resulting from 15 bitrate-resolution pairs were used for subjective evaluation. A total of 25 participants rated all the 90 PVSs.

KUGVD: Six SRCs out of the 24 SRCs from the GVSwere used to develop KUGVD. The same bitrate-resolution pairs from GVS were included to define the HRCs. In total, 90 PVSs were used in the subjective evaluation and 17 participants took part in the test.

CGVDS:  This dataset consists of SRCs captured at 60fps from 15 different games. For designing the HRCs, three resolutions, namely, 480p, 720p and 1080p at three different framerates of 20, 30, and 60fps were considered. To ensure that the SRCs from all the games could be assessed by test subjects, the overall test was split into 5 different subjective tests, with a minimum of 72 PVSs being rated in each of the tests. A total of over 100 participants took part over the five different tests, with a minimum of 20 participants per test.

Twitch: The Twitch Dataset consists of 36 different games, with 6 games each representing one out of 6 pre-defined genres. The dataset consists of streams directly downloaded from Twitch. A total of 351 video sequences of approximately 50s duration across all representations were downloaded. 90 video sequences out of these 351 video sequences were selected for subjective evaluation. Only the first 30s of the chosen 90 PVSs were considered for subjective testing. Six different resolutions between 160p and 1080p at framerates of 30 and 60fps were used. 29 participants rated all the 90 PVSs.

BBQCG: This is the training dataset developed as part of the P.BBQCG work item. This dataset consists of nine subjective test databases. Three out of these nine test databases consisted of processed video sequences (PVSs) up to 1080p/120fps and the remaining had PVSs up to 4K/60fps. Three codecs, namely, H.264, H.265, and AV1 were used to encode the videos. Overall 900 different PVSs were created from 12 sources (SRCs) by encoding the SRCs with different encoding settings.

AVT-VQDB-UHD-1-VD: This dataset consists of 16 source contents encoded using a CRF-based encoding approach. Overall 192 PVSs were generated by encoding all 16 sources in four resolutions, namely, 360p, 720p, 1080p, 2160p with three CRF values (22, 30, 38) each. A total of 40 subjects participate in the study.

ITU-T P.1204.1 and P.1204.2 model prediction performance

The performance figures of the two new models P.1204.1 and P.1204.2 models on the different datasets are indicated in Table 1 (P.1204.1) and Table 2 (P.1204.2) below.

For all databases except BBQCG and KUGVD, the Mode 0 model P.1204.1 performs in a solid way, as shown in Table 1. With the information about frame types and sizes available to the Mode 1 model P.1204.2, performance improves considerably, as shown in Table 2. For performance results of all three previously standardized models, P.1204.3, P.1204.4 and P.1204.5, the reader is referred to [1] and the individual standards, [4][5][6]. For the P.1204.3 model, complementary performance information is presented in, e.g., [2][7]. For P.1204.4, additional model performance information is available in [8], including results for AV1, AVS2, and VVC.

The following plots provide an illustration of how the new P.1204.1 Mode 0 model may be used. Here, bitrate-ladder-type graphs are presented, with the predicted Mean Opinion Score on a 5-point scale plotted over log bitrate.

Codec: H.264

Codec: H.265

Codec: VP9

Conclusions and Outlook

The P.1204 standard series now comprises the complete initially planned set of models, namely:

• ITU-T P.1204.1: Bitstream Mode 0, i.e., metadata-based model with access to information about video codec, resolution, framerate and bitrate used.
• ITU-T P.1204.2: Bitstream Mode 1, i.e., metadata-based model with access to information about video codec, resolution, framerate and bitrate used, plus information about video frame types and sizes.
• ITU-T P.1204.3: Bitstream Mode 3 [1][2][3][7].
• ITU-T P.1204.4: Pixel-based reduced- and full-reference [1][5][8].
• ITU-T P.1204.5: Hybrid no-reference Mode 0 [1][6].

Extensions of some of these models beyond the initial scope of codecs (H.264/AVC, H.265/HEVC, VP9) have been included over the last few years. Here, P.1204.4 and P.1204.5 have been extended (P.1204.5) or evaluated (P.1204.4) to also cover the AV1 video codec. Work in ITU-T SG12 (Q14/12) is ongoing so as to also extend P.1204.1, P.1204.2 and P.1204.3 to newer codecs such as AV1, and all five models are planned to be extended so as to also cover VVC. It is noted that for P.1204.3, P.1204.4 and P.1204.5, also long-term quality integration modules that generate per-session scores for up to 5min long streaming sessions have been described in Appendices of the respective recommendations. For P.1204.1 and P.1204.2, this extension still has to be completed. Initial evaluations for similar Mode 0 and Mode 1 models that use the P.1204.3-type long-term integration can be found in [7].

References

[1] Raake, A., Borer, S., Satti, S.M., Gustafsson, J., Rao, R.R.R., Medagli, S., List, P., Göring, S., Lindero, D., Robitza, W. and Heikkilä, G., 2020. Multi-model standard for bitstream-, pixel-based and hybrid video quality assessment of UHD/4K: ITU-T P. 1204. IEEE Access, 8, pp.193020-193049.
[2] Rao, R.R.R., Göring, S., List, P., Robitza, W., Feiten, B., Wüstenhagen, U. and Raake, A., 2020, May. Bitstream-based model standard for 4K/UHD: ITU-T P. 1204.3—Model details, evaluation, analysis and open source implementation. In 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX) (pp. 1-6).
[3] ITU-T Rec. P.1204, 2025. Video quality assessment of streaming services over reliable transport for resolutions up to 4K. International Telecommunication Union (ITU-T), Geneva, Switzerland.
[4] ITU-T Rec. P.1204.3, 2020. Video quality assessment of streaming services over reliable transport for resolutions up to 4K with access to full bitstream information. International Telecommunication Union (ITU-T), Geneva, Switzerland.
[5] ITU-T Rec. P.1204.4, 2022. Video quality assessment of streaming services over reliable transport for resolutions up to 4K with access to full and reduced reference pixel information. International Telecommunication Union (ITU-T), Geneva, Switzerland.
[6] ITU-T Rec. P.1204.5, 2023. Video quality assessment of streaming services over reliable transport for resolutions up to 4K with access to transport and received pixel information. International Telecommunication Union (ITU-T), Geneva, Switzerland.
[7] Rao, R.R.R., Göring, S. and Raake, A., 2022. AVQBits – Adaptive video quality model based on bitstream information for various video applications. IEEE Access, 10, pp.80321-80351.
[8] Borer, S., 2022, September. Performance of ITU-T P. 1204.4 on Video Encoded with AV1, AVS2, VVC. In 2022 14th International Conference on Quality of Multimedia Experience (QoMEX) (pp. 1-4).
[9] Winkler, S. and Mohandas, P., 2008. The evolution of video quality measurement: From PSNR to hybrid metrics. IEEE transactions on Broadcasting, 54(3), pp.660-668.
[10] Wang, Z., Lu, L. and Bovik, A.C., 2004. Video quality assessment based on structural distortion measurement. Signal Processing: Image Communication, 19(2), pp.121-132.
[11] Li, Z., Aaron, A., Katsavounidis, I., Moorthy, A., and Manohara, M., 2016. Toward A Practical Perceptual Video Quality Metric, Netflix TechBlog.
[12] Li, Z., Swanson, K., Bampis, C., Krasula, L., and Aaron, A., 2020. Toward a Better Quality Metric for the Video Community, Netflix TechBlog.

The 152nd MPEG meeting took place in Geneva, Switzerland, from October 7 to October 11, 2025. The official MPEG press release can be found here. This column highlights key points from the meeting, amended with research aspects relevant to the ACM SIGMM community:

• MPEG Systems received an Emmy® Award for the Common Media Application Format (CMAF). A separate press release regarding this achievement is available here.
• JVET ratified new editions of VSEI, VVC, and HEVC
• The fourth edition of Visual Volumetric Video-based Coding (V3C and V-PCC) has been finalized
• Responses to the call for evidence on video compression with capability beyond VVC successfully evaluated

MPEG Systems received an Emmy® Award for the Common Media Application Format (CMAF)

On September 18, 2025, the National Academy of Television Arts & Sciences (NATAS) announced that the MPEG Systems Working Group (ISO/IEC JTC 1/SC 29/WG 3) had been selected as a recipient of a Technology & Engineering Emmy® Award for standardizing the Common Media Application Format (CMAF). But what is CMAF? CMAF (ISO/IEC 23000-19) is a media format standard designed to simplify and unify video streaming workflows across different delivery protocols and devices. Here’s a structured overview. Before CMAF, streaming services often had to produce multiple container formats, i.e., (i) ISO Base Media File Format (ISOBMFF) for MPEG-DASH and MPEG-2 Transport Stream (TS) for Apple HLS. This duplication resulted in additional encoding, packaging, and storage costs. I wrote a blog post about this some time ago here. CMAF’s main goal is to define a single, standardized segmented media format usable by both HLS and DASH, enabling “encode once, package once, deliver everywhere.”

The core concept of CMAF is that it is based on ISOBMFF, the foundation for MP4. Each CMAF stream consists of a CMAF header, CMAF media segments, and CMAF track files (a logical sequence of segments for one stream, e.g., video or audio). CMAF enables low-latency streaming by allowing progressive segment transfer, adopting chunked transfer encoding via CMAF chunks. CMAF defines interoperable profiles for codecs and presentation types for video, audio, and subtitles. Thanks to its compatibility with and adoption within existing streaming standards, CMAF bridges the gaps between DASH and HLS, creating a unified ecosystem.

Research aspects include – but are not limited to – low-latency tuning (segment/chunk size trade-offs, HTTP/3, QUIC), Quality of Experience (QoE) impact of chunk-based adaptation, synchronization of live and interactive CMAF streams, edge-assisted CMAF caching and prediction, and interoperability testing and compliance tools.

JVET ratified new editions of VSEI, VVC, and HEVC

At its 40th meeting, the Joint Video Experts Team (JVET, ISO/IEC JTC 1/SC 29/WG 5) concluded the standardization work on the next editions of three key video coding standards, advancing them to the Final Draft International Standard (FDIS) stage. Corresponding twin-text versions have also been submitted to ITU-T for consent procedures. The finalized standards include:

• Versatile Supplemental Enhancement Information (VSEI) — ISO/IEC 23002-7 | ITU-T Rec. H.274
• Versatile Video Coding (VVC) — ISO/IEC 23090-3 | ITU-T Rec. H.266
• High Efficiency Video Coding (HEVC) — ISO/IEC 23008-2 | ITU-T Rec. H.265

The primary focus of these new editions is the extension and refinement of Supplemental Enhancement Information (SEI) messages, which provide metadata and auxiliary data to support advanced processing, interpretation, and quality management of coded video streams.

The updated VSEI specification introduces both new and refined SEI message types supporting advanced use cases:

• AI-driven processing: Extensions for neural-network-based post-filtering and film grain synthesis offer standardized signalling for machine learning components in decoding and rendering pipelines.
• Semantic and multimodal content: New SEI messages describe infrared, X-ray, and other modality indicators, region packing, and object mask encoding; creating interoperability points for multimodal fusion and object-aware compression research.
• Pipeline optimization: Messages defining processing order and post-processing nesting support research on joint encoder-decoder optimization and edge-cloud coordination in streaming architectures.
• Authenticity and generative media: A new set of messages supports digital signature embedding and generative-AI-based face encoding, raising questions for the SIGMM community about trust, authenticity, and ethical AI in media pipelines.
• Metadata and interpretability: New SEIs for text description, image format metadata, and AI usage restriction requests could facilitate research into explainable media, human-AI interaction, and regulatory compliance in multimedia systems.

All VSEI features are fully compatible with the new VVC edition, and most are also supported in HEVC. The new HEVC edition further refines its multi-view profiles, enabling more robust 3D and immersive video use cases.

Research aspects of these new standard’s editions can be summarized as follows: (i) Define new standardized interfaces between neural post-processing and conventional video coding, fostering reproducible and interoperable research on learned enhancement models. (ii) Encourage exploration of metadata-driven adaptation and QoE optimization using SEI-based signals in streaming systems. (iii) Open possibilities for cross-layer system research, connecting compression, transport, and AI-based decision layers. (iv) Introduce a formal foundation for authenticity verification, content provenance, and AI-generated media signalling, relevant to current debates on trustworthy multimedia.

These updates highlight how ongoing MPEG/ITU standardization is evolving toward a more AI-aware, multimodal, and semantically rich media ecosystem, providing fertile ground for experimental and applied research in multimedia systems, coding, and intelligent media delivery.

The fourth edition of Visual Volumetric Video-based Coding (V3C and V-PCC) has been finalized

MPEG Coding of 3D Graphics and Haptics (ISO/IEC JTC 1/SC 29/WG7) has advanced MPEG-I Part 5 – Visual Volumetric Video-based Coding (V3C and V-PCC) to the Final Draft International Standard (FDIS) stage, marking its fourth edition. This revision introduces major updates to the Video-based Coding of Volumetric Content (V3C) framework, particularly enabling support for an additional bitstream instance: V-DMC (Video-based Dynamic Mesh Compression).

Previously, V3C served as the structural foundation for V-PCC (Video-based Point Cloud Compression) and MIV (MPEG Immersive Video). The new edition extends this flexibility by allowing V-DMC integration, reinforcing V3C as a generic, extensible framework for volumetric and 3D video coding. All instances follow a shared principle, i.e., using conventional 2D video codecs (e.g., HEVC, VVC) for projection-based compression, complemented by specialized tools for mapping, geometry, and metadata handling.

While V-PCC remains co-specified within Part 5, MIV (Part 12) and V-DMC (Part 29) are standardized separately. The progression to FDIS confirms the technical maturity and architectural stability of the framework.

This evolution opens new research directions as follows: (i) Unified 3D content representation, enabling comparative evaluation of point cloud, mesh, and view-based methods under one coding architecture. (ii) Efficient use of 2D codecs for 3D media, raising questions on mapping optimization, distortion modeling, and geometry-texture compression. (iii) Dynamic and interactive volumetric streaming, relevant to AR/VR, telepresence, and immersive communication research.

The fourth edition of MPEG-I Part 5 thus positions V3C as a cornerstone for future volumetric, AI-assisted, and immersive video systems, bridging standardization and cutting-edge multimedia research.

Responses to the call for evidence on video compression with capability beyond VVC successfully evaluated

The Joint Video Experts Team (JVET, ISO/IEC JTC 1/SC 29/WG 5) has completed the evaluation of submissions to its Call for Evidence (CfE) on video compression with capability beyond VVC. The CfE investigated coding technologies that may surpass the performance of the current Versatile Video Coding (VVC) standard in compression efficiency, computational complexity, and extended functionality.

A total of five submissions were assessed, complemented by ECM16 reference encodings and VTM anchor sequences with multiple runtime variants. The evaluation addressed both compression capability and encoding runtime, as well as low-latency and error-resilience features. All technologies were derived from VTM, ECM, or NNVC frameworks, featuring modified encoder configurations and coding tools rather than entirely new architectures.

Key Findings

• In the compression capability test, 76 out of 120 test cases showed at least one submission with a non-overlapping confidence interval compared to the VTM anchor. Several methods outperformed ECM16 in visual quality and achieved notable compression gains at lower complexity. Neural-network-based approaches demonstrated clear perceptual improvements, particularly for 8K HDR content, while gains were smaller for gaming scenarios.
• In the encoding runtime test, significant improvements were observed even under strict complexity constraints: 37 of 60 test points (at both 1× and 0.2× runtime) showed statistically significant benefits over VTM. Some submissions achieved faster encoding than VTM, with only a 35% increase in decoder runtime.

Research Relevance and Outlook

The CfE results illustrate a maturing convergence between model-based and data-driven video coding, raising research questions highly relevant for the ACM SIGMM community:

• How can learned prediction and filtering networks be integrated into standard codecs while preserving interoperability and runtime control?
• What methodologies can best evaluate perceptual quality beyond PSNR, especially for HDR and immersive content?
• How can complexity-quality trade-offs be optimized for diverse hardware and latency requirements?

Building on these outcomes, JVET is preparing a Call for Proposals (CfP) for the next-generation video coding standard, with a draft planned for early 2026 and evaluation through 2027. Upcoming activities include refining test material, adding Reference Picture Resampling (RPR), and forming a new ad hoc group on hardware implementation complexity.

For multimedia researchers, this CfE marks a pivotal step toward AI-assisted, complexity-adaptive, and perceptually optimized compression systems, which are considered a key frontier where codec standardization meets intelligent multimedia research.

The 153rd MPEG meeting will be held online from January 19 to January 23, 2026. Click here for more information about MPEG meetings and their developments.

JPEG XE reaches Committee Draft stage at the 108th JPEG meeting

The 108th JPEG meeting was held in Daejeon, Republic of Korea, from 29 June to 4 July 2025.

During this meeting, the JPEG Committee finalised the Committee Draft of JPEG XE, an upcoming International Standard for lossless coding of visual events, that has been sent for consultation of ISO/IEC JTC1/SC29 national bodies. JPEG XE will be the first International Standard developed for the lossless representation and coding of visual events, and is being developed under the auspices of ISO, IEC, and ITU.

Furthermore, the JPEG Committee was informed that the prestigious Joseph von Fraunhofer Prize 2025 was awarded to three JPEG Committee members Prof. Siegfried Fößel, Dr. Joachim Keinert and Dr. Thomas Richter, for their contributions to the development of the JPEG XS standard. The JPEG XS standard specifies a compression technology with very low latency at a low implementation complexity and with a very precise bit-rate control. A presentation video can be accessed here.

The following sections summarise the main highlights of the 108th JPEG meeting:

• JPEG XE Committee Draft sent for consultation
• JPEG Trust second edition aligns with C2PA
• JPEG AI parts 2, 3 and 4 proceed for publication as IS
• JPEG DNA reaches DIS stage
• JPEG AIC on Objective Image Quality Assessment
• JPEG Pleno Learning-based Point Cloud Coding proceed for publication as IS
• JPEG XS Part 1 Amendment 1 proceeds to DIS stage
• JPEG RF explores 3DGS coding and quality evaluation

JPEG XE

At the 108th JPEG Meeting, the Committee Draft of the first International Standard for lossless coding of events was issued and sent for consultation to ISO/IEC JTC1/SC29 national bodies for consultation. JPEG XE is being developed under the auspices of ISO/IEC and ITU-T and aims to establish a robust and interoperable format for efficient representation and coding of events in the context of machine vision and related applications. By reaching the Committee Draft stage, the JPEG Committee has attained a very important milestone. The Committee Draft was produced based on the five received responses to a Call for Proposals issued after the 104th JPEG Meeting held in July 2024. The two submissions meet the requirements for the constrained lossless coding of events and allow the implementation and operation of the coding model with limited resources, power, and complexity. The remaining three responses address the unconstrained coding mode and will be considered in a second phase of standardisation.

JPEG XE is the fruit of a joint effort between ISO/IEC JTC1/SC29/WG1 and ITU-T SG21 and is hoped to result in a largely supported JPEG XE standard, improving the potential compatibility and interoperability across applications, products, and services. Additionally, the JPEG Committee is in contact with the MIPI Alliance with the intention of developing a cross-compatible coding mode, allowing MIPI ESP signals to be decoded effectively by JPEG XE decoders.

The JPEG Committee remains committed to the development of a comprehensive and industry-aligned standard that meets the growing demand for event-based vision technologies. The collaborative approach between multiple standardisation organisations underscores a shared vision for a unified, international standard to accelerate innovation and interoperability in this emerging field.

JPEG Trust

JPEG Trust completed its second edition of JPEG Trust Part 1: Core Foundation, which brings JPEG Trust into alignment with the updated C2PA specification 2.1 and integrates aspects of Intellectual Property Rights (IPR). This second edition is now approved as a Draft International Standard for submission to ISO/IEC balloting, with an expected completion timeframe at the end of 2025.

Showcasing the adoption of JPEG Trust technology, JPEG Trust Part 4 – Reference software has now reached the Committee Draft stage.

Work continues on JPEG Trust Part 2: Trust profiles catalogue, a repository of Trust Profile and reporting snippets designed to assist implementers in constructing their Trust Profiles and Trust Reports, as well as JPEG Trust Part 3: Media asset watermarking.

JPEG AI

During the 108th JPEG meeting, JPEG AI Parts 2, 3, and 5 received positive DIS ballot results with only editorial comments, allowing them to proceed to publication as International Standards. These parts extend Part 1 by specifying stream and decoder profiles, reference software with usage documentation, and file format embedding for container formats such as ISOBMFF and HEIF.

The results from two Core Experiments were reviewed. The first evaluated gain map-based HDR coding, comparing it to simulcast methods and HEIC, while the second focused on implementing JPEG AI on smartphones using ONNX. Progressive decoding performance was assessed under channel truncation, and adaptive selection techniques were proposed to mitigate losses. Subjective and objective evaluations confirmed JPEG AI’s strong performance, often surpassing codecs such as VVC Intra, AVIF, JPEG XL, and performing comparably to ECM in informal viewing tests.

Another contribution explored compressed-domain image classification using latent representations, demonstrating competitive accuracy across bitrates. A proposal to limit tile splits in JPEG AI Part 2 was also discussed, and experiments identified Model 2 as the most robust and efficient default model for the levels with only one model at the decoder side.

JPEG DNA

During the 108th JPEG meeting, the JPEG Committee produced a study DIS text of JPEG DNA Part 1 (ISO/IEC 25508-1). The purpose of this text is to synchronise the current version of the Verification Model with the changes made to the Committee Draft document, reflecting the comments received from the consultation. The DIS balloting of Part 1 is scheduled to take place after the next JPEG meeting, starting in October 2025.

The JPEG Committee is also planning wet-lab experiments to validate that the current specification of the JPEG DNA satisfies the conditions required for applications using the current state of the art in DNA synthesis and sequencing, such as biochemical constraints, decodability, coverage rate, and the impact of error-correcting code on compression performance.

The goal still remains to reach International Standard (IS) status for Part 1 during 2026.

JPEG AIC

Part 4 of JPEG AIC deals with objective quality metrics for fine-grained assessment of high-fidelity compressed images. As of the 108th JPEG Meeting, the Call for Proposals on Objective Image Quality Assessment (JPEG AIC-4), which was launched in April 2025, has already resulted in four non-mandatory registrations of interest that were reviewed. In this JPEG meeting, the technical details regarding the evaluation of proposed metrics and of the anchor metrics were developed and finalised. The results have been integrated in the document “Common Test Conditions on Objective Image Quality Assessment v2.0”, available on the JPEG website. Moreover, the procedures to generate the evaluation image dataset were defined and will be carried out by JPEG experts. The responses to the Call for Proposals for JPEG AIC-4 are expected in September 2025, together with their application for the evaluation dataset, with the goal of creating a Working Draft of a new standard on objective quality assessment of high-fidelity images by April 2026.

JPEG Pleno

At the 108th JPEG meeting, significant progress was reported in the ongoing JPEG Pleno Quality Assessment activity for light fields. A Call for Proposals (CfP) on objective quality metrics for light fields is currently underway, with submissions to be evaluated using a new evaluation dataset. The JPEG Committee also prepares the DIS of ISO/IEC 21794-7, which defines a standard for subjective quality assessment methodologies of light fields.

During the 108th JPEG meeting, the 2nd edition of ISO/IEC 21794-2 (“Plenoptic image coding system (JPEG Pleno) Part 2: Light field coding”) advanced to the Draft International Standard (DIS) stage. This 2nd edition includes the specification of a third coding mode entitled Slanted 4D Transform Mode and its associated profile.

The 108th JPEG meeting also saw the successful completion of the Final Draft International Standard balloting and the impending publication of ISO/IEC 21794-6: Learning-based Point Cloud Coding. This is the world’s first international standard on learning-based point cloud coding. The publication of Part 6 of ISO/IEC 21794 is a crucial and notable milestone in the representation of point clouds. The publication of the International Standard is expected to take place during the second half of 2025.

JPEG XS

The JPEG Committee advanced the AMD 1 of JPEG XS Part 1 to DIS stage; it allows the embedding of sub-frame metadata to JPEG XS as required by augmented and virtual reality applications currently discussed within VESA. Part 5 3rd edition, which is the reference software of JPEG XS, was also approved for publication as an International Standard.

JPEG RF

During the 108th JPEG meeting, the JPEG Radiance Fields exploration advanced its work on discussing the procedures for reliable evaluation of potential proposals in the future, with a particular focus on refining subjective evaluation protocols. A key outcome was the initiation of Exploration Study 5, aimed at investigating how different test camera trajectories influence human perception during subjective quality assessment. The Common Test Conditions (CTC) document was also reviewed, with the subjective testing component remaining provisional pending the outcome of this exploration study. In addition, existing use cases and requirements for JPEG RF were re-examined, setting the stage for the development of revised drafts of both the Use Cases and Requirements document and the CTC. New mandates include conducting Exploration Study 5, revising documents, and expanding stakeholder engagement.

Final Quote

“The release of the Committee Draft of JPEG XE standard for lossless coding of events at the 108th JPEG meeting is an impressive achievement and will accelerate deployment of products and applications relying on visual events.” said Prof. Touradj Ebrahimi, the Convenor of the JPEG Committee.