Signal Processing: Image Communication is an international journal for the development of the theory and practice of image communication. Its primary objectives are the following:

To present a forum for the advancement of theory and practice of image communication.

To stimulate cross-fertilization between areas similar in nature which have traditionally been separated, for example, various aspects of visual communications and information systems.

To contribute to a rapid information exchange between the industrial and academic environments.

The editorial policy and the technical content of the journal are the responsibility of the Editor-in-Chief, the Area Editors and the Advisory Editors. The Journal is self-supporting from subscription income and contains a minimum amount of advertisements. Advertisements are subject to the prior approval of the Editor-in-Chief. The journal welcomes contributions from every country in the world.

Signal Processing: Image Communication publishes articles relating to aspects of the design, implementation and use of image communication systems. The journal features original research work, tutorial and review articles, and accounts of practical developments.

Subjects of interest include:

    Multimedia coding, 3D and multi-view compression for human and machine consumption
    3D and multi-view representations, multimedia pre/post processing, video restoration and super-resolution, video synthesis
    Peer-to-peer video networking, wireless video broadcasting and communication, visual surveillance, video processing for automation and remote operation, architectures for image/video processing and communication
    Interactive visual communication, Virtual Reality (VR), Augmented Reality (AR) and eXtended Reality (XR) systems, point cloud processing and compression, light field capture and rendering, immersive media technologies, real-time 3D environment reconstruction
    Multimedia quality assessment and measures, models for QoS and QoE
    Multi-camera video analysis, motion analysis, content-based media indexing and retrieval, semantics, face and gesture processing

Special Issue on Learned Visual data Coding – Emerging Paradigms and Future Directions
提出日: 2025-10-01

The rapid proliferation of visual data in today’s digital world demands innovative, intelligent, and adaptable compression solutions. Traditional codecs like JPEG, H.264/AVC, HEVC, and VVC—built on hand-crafted algorithms—have served well but struggle to meet modern needs for scalability and integration. Recent breakthroughs in machine learning have enabled learned visual data coding, where deep neural networks replace or enhance conventional components with data-driven, end-to-end models. These approaches show promising rate-distortion performance, especially in task-specific or constrained scenarios. This Special Issue invites contributions advancing this transformative field.
Topics of interest include, but are not limited to:

    End-to-end learned image/video compression models
    Neural transforms, quantization, and entropy coding
    Coding for machine
    Cross-domain and cross-modal coding (e.g., text+image, video+audio)
    Learned compression for emerging data formats (e.g., point clouds, light fields, volumetric video)
    Low-latency and real-time learned codecs
    Rate-distortion optimization and perceptual quality metrics for learned codecs
    Hardware-friendly and efficient neural compression models
    Benchmarking and evaluation of learned codecs
    Applications of learned coding in bandwidth-limited and edge environments

Guest editors:
Dr. Alessandro Gnutti
Università degli Studi di Brescia, Brescia, Italy
Dr. Wen-Hsiao Peng
National Yang Ming Chiao Tung University, Hsinchu, Taiwan

Manuscript submission information:

    Open for Submission: from 01-Jul-2025 to 01-Oct-2025
    Submission Site: Editorial Manager®
    Article Type Name: "VSI: IMAGE_Visual Data Coding" - please select this item when you submit manuscripts online

All manuscripts will be peer-reviewed. Submissions will be evaluated based on originality, significance, technical quality, and clarity. Once accepted, articles will be posted online immediately and published in a journal regular issue within weeks. Articles will also be simultaneously collected in the online special issue.

For any inquiries about the appropriateness of contribution topics, welcome to contact Leading Guest Editor (mailto: Email Address).

Guide for Authors will be helpful for your future contributions, read more: Guide for authors - Signal Processing: Image Communication - ISSN 0923-5965 | ScienceDirect.com by Elsevier

For more information about our Journal, please visit our ScienceDirect Page: Signal Processing: Image Communication | Journal | ScienceDirect.com by Elsevier

Keywords:

    Learned image/video compression; 
    Coding for machine; 
    Visual data coding; 
    Deep neural networks for compression; 
    Task-aware compression; Cross-domain visual coding

Special Issue on Immersive and networked media for next-gen communications
提出日: 2025-10-15

In recent years, Extended Reality (XR) systems are experiencing an unprecedented diffusion. The availability of relatively low-cost devices, together with an increasing number of applications calling for high quality XR content has pushed the research community to investigate and develop new XR solutions. In parallel, the increase of bandwidth availability and in-network computational capability is fostering the realization of collaborative and interactive immersive applications thus opening a new era of communication services.

To support the development of fully immersive communication systems many challenges are yet to be tackled. This includes on the one hand the generation of the XR content, and the subsequent adoption and perception by the user. In addition, for networked applications, another key element is in the delivery of the XR content, coping with bandwidth and timing constraints. This is particularly relevant since, while XR experiences become more realistic, the complexity of rendering virtual scenes is growing beyond the capabilities of compact headsets, thus requiring finding a suitable trade-off between the local processing and the off-load to cloud-based services. In such scenarios, predictive compression and resource allocation techniques must be envisaged. These challenges become even more complex to tackle when multi-user and real-time services are involved. Furthermore, the ultimate success of XR solutions is up to the final user whose expectations must be fulfilled. Based on this, the Quality of Experience (QoE) aspects in terms of feeling of immersion and presence, quality of interaction and overall usability and accessibility are of utmost importance. Therefore, the definition of QoE-aware XR solutions is needed. Finally, as for other network-based multimedia services, the security aspects cannot be disregarded. To address these challenges, this special issue welcomes contributions on the following topics:

    XR content generation and rendering (e.g., omni-directional images and videos, pointclouds, 3D meshes, AI-generated content)
    QoE-aware compression and transmission techniques (e.g., predictive and adaptive techniques)
    User modelling (e.g., physical tracking, avatar generation, emotional understanding)
    QoE methodologies for XR
    Secure XR communications (e.g., identification and authentication techniques, content authenticity control)

The special issue will be open to all contributors of the research community and will leverage the critical mass of the FUN-Media project which specifically addresses immersive media communications over networks. FUN-Media is one of the core projects of RESTART (“RESearch and innovation on future Telecommunications systems and networks, to make Italy more smart”) – an initiative funded under the NextGeneration EU framework representing

Guest editors:
Prof. Nicola Conci
Università di Trento, Trento, Italy
Dr. Sara Baldoni
Università degli Studi di Padova, Padua, Italy

Manuscript submission information:

    Guest Editor Invitation Only
    Open for Submission: from 27-Jul-2025 to 15-Oct-2025
    Submission Site: Editorial Manager®
    Article Type Name: "VSI: IMAGE_Immersive and Networked Media" - please select this item when you submit manuscripts online

All manuscripts will be peer-reviewed. Submissions will be evaluated based on originality, significance, technical quality, and clarity. Once accepted, articles will be posted online immediately and published in a journal regular issue within weeks. Articles will also be simultaneously collected in the online special issue.

For any inquiries about the appropriateness of contribution topics, welcome to contact Leading Guest Editor  

Guide for Authors will be helpful for your future contributions, read more: Guide for authors - Signal Processing: Image Communication - ISSN 0923-5965 | ScienceDirect.com by Elsevier

For more information about our Journal, please visit our ScienceDirect Page: Signal Processing: Image Communication | Journal | ScienceDirect.com by Elsevier

Keywords:

    Extended Reality; 
    Omni-directional images and videos; 
    Pointclouds; 3D meshes; 
    AI-generated content; 
    Quality of Experience; 
    QoE-aware compression and transmission; 
    Avatar generation; 
    Emotional understanding; 
    Content authenticity control