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Electronics
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Recent Advances in Image/Video Compression and Coding
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Recent Advances in Image/Video Compression and Coding

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 15 February 2025 | Viewed by 2126

Special Issue Editors

Dr. Miroslav Uhrina

E-Mail Website
Guest Editor
Department of Multimedia and Information and Communication Technology, Faculty of Electrical Engineering and Information Technology, University of Zilina, Univerzitna 1, 010 26 Zilina, Slovakia
Interests: audio and video compression; quality of experience (QoE); TV broadcasting; IP networks
Special Issues, Collections and Topics in MDPI journals
Dr. Jaroslav Frnda

E-Mail Website
Guest Editor
Department of Quantitative Methods and Economic Informatics, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Univerzitna 1, 010 26 Zilina, Slovakia
Interests: quality of multimedia services; machine learning algorithms; data analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Lukas Sevcik

E-Mail Website
Guest Editor
Department of Multimedia and Information and Communication Technology, Faculty of Electrical Engineering and Information Technology, University of Zilina, Univerzitna 1, 010 26 Zilina, Slovakia
Interests: multimedia communication; information communication; computer networks; quality of service (QoS); quality of experience (QoE)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recently, the demand for multimedia services, especially in the video domain, has rapidly increased. The need for higher resolution, framerate and sampling precision grows annually, with 4K resolution becoming a common part of video broadcasting and streaming. Indeed, the research community nowadays aspires toward on 8K resolution. The demand for higher framerate has also risen in the last years, especially from companies dealing with video postproduction. Last but not least, the high dynamic range (HDR) technique, as a common feature which can boost image and video quality, has come to the fore. On the one hand, all these parameters can improve an observer´s experience; conversely, they exert a large impact on the final bitrate and bandwidth. Such huge quantities of data are processed, stored or transmitted. This represents a major challenge for industry, encouraging researchers and companies to develop new compression techniques and standards. Newly developed codecs should reduce the amount of data and keep perceived quality at the same level.

This Special Issue focuses on the theoretical and practical design issues of video compression and coding. Our aim is to bring together researchers, industry experts and companies working in the related areas to share their new ideas, latest findings, and state-of-the-art achievements with others.

The topics of interest include, but are not limited to:

  • Image coding and compression;
  • Video coding and compression;
  • Machine learning in image and video coding;
  • Coding techniques for 3D and immersive video;
  • Quality of service (QoS);
  • Quality of experience (QoE);
  • Machine learning in QoS and QoE;
  • Adaptive bitrate streaming.

Dr. Miroslav Uhrina
Dr. Jaroslav Frnda
Dr. Lukas Sevcik
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • image and video coding
  • image and video compression
  • multimedia communication
  • machine learning
  • QoE
  • QoS
  • video streaming

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Published Papers (2 papers)

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34 pages, 2908 KiB  
Article
A Hybrid Contrast and Texture Masking Model to Boost High Efficiency Video Coding Perceptual Rate-Distortion Performance
by Javier Ruiz Atencia, Otoniel López-Granado, Manuel Pérez Malumbres, Miguel Martínez-Rach, Damian Ruiz Coll, Gerardo Fernández Escribano and Glenn Van Wallendael
Electronics 2024, 13(16), 3341; https://doi.org/10.3390/electronics13163341 - 22 Aug 2024
Viewed by 571
Abstract
As most of the videos are destined for human perception, many techniques have been designed to improve video coding based on how the human visual system perceives video quality. In this paper, we propose the use of two perceptual coding techniques, namely contrast [...] Read more.
As most of the videos are destined for human perception, many techniques have been designed to improve video coding based on how the human visual system perceives video quality. In this paper, we propose the use of two perceptual coding techniques, namely contrast masking and texture masking, jointly operating under the High Efficiency Video Coding (HEVC) standard. These techniques aim to improve the subjective quality of the reconstructed video at the same bit rate. For contrast masking, we propose the use of a dedicated weighting matrix for each block size (from 4×4 up to 32×32), unlike the HEVC standard, which only defines an 8×8 weighting matrix which it is upscaled to build the 16×16 and 32×32 weighting matrices (a 4×4 weighting matrix is not supported). Our approach achieves average Bjøntegaard Delta-Rate (BD-rate) gains of between 2.5% and 4.48%, depending on the perceptual metric and coding mode used. On the other hand, we propose a novel texture masking scheme based on the classification of each coding unit to provide an over-quantization depending on the coding unit texture level. Thus, for each coding unit, its mean directional variance features are computed to feed a support vector machine model that properly predicts the texture type (plane, edge, or texture). According to this classification, the block’s energy, the type of coding unit, and its size, an over-quantization value is computed as a QP offset (DQP) to be applied to this coding unit. By applying both techniques in the HEVC reference software, an overall average of 5.79% BD-rate gain is achieved proving their complementarity. Full article
(This article belongs to the Special Issue Recent Advances in Image/Video Compression and Coding)
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18 pages, 512 KiB  
Article
Fast Coding Unit Partitioning Algorithm for Video Coding Standard Based on Block Segmentation and Block Connection Structure and CNN
by Nana Li, Zhenyi Wang and Qiuwen Zhang
Electronics 2024, 13(9), 1767; https://doi.org/10.3390/electronics13091767 - 2 May 2024
Viewed by 1071
Abstract
The recently introduced Video Coding Standard, VVC, presents a novel Quadtree plus Nested Multi-Type Tree (QTMTT) block structure. This structure enables a more flexible block partition and demonstrates enhanced compression performance compared to its predecessor, HEVC. However, The introduction of the new structure [...] Read more.
The recently introduced Video Coding Standard, VVC, presents a novel Quadtree plus Nested Multi-Type Tree (QTMTT) block structure. This structure enables a more flexible block partition and demonstrates enhanced compression performance compared to its predecessor, HEVC. However, The introduction of the new structure has led to a more complex partition search process, resulting in a considerable increase in time complexity. The QTMTT structure yields diverse Coding Unit (CU) block sizes, posing challenges for CNN model inference. In this study, we propose a representation structure termed Block Segmentation and Block Connection (BSC), rooted in texture features. This ensures that partial CU blocks are uniformly represented in size. To address different-sized CUs, various levels of CNN models are designed for prediction. Moreover, we introduce a post-processing method and a multi-thresholding scheme to further mitigate errors introduced by CNNs. This allows for flexible and adjustable acceleration, achieving a trade-off between coding time complexity and performance. Experimental results indicate that, in comparison to VTM-10.0, our “Fast” scheme reduces the average complexity by 57.14% with a 1.86% increase in BDBR. Meanwhile, the “Moderate” scheme reduces average complexity by 50.14% with only a 1.39% increase in BDBR. Full article
(This article belongs to the Special Issue Recent Advances in Image/Video Compression and Coding)
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