Yipeng Liu;Qi Yang;Yujie Zhang;Yiling Xu;Le Yang;Xiaozhong Xu;Shan Liu
{"title":"Once-Training-All-Fine: No-Reference Point Cloud Quality Assessment via Domain-Relevance Degradation Description","authors":"Yipeng Liu;Qi Yang;Yujie Zhang;Yiling Xu;Le Yang;Xiaozhong Xu;Shan Liu","doi":"10.1109/TBC.2025.3541862","DOIUrl":"https://doi.org/10.1109/TBC.2025.3541862","url":null,"abstract":"The visual quality of point clouds plays a crucial role in the development and broadcasting of immersive media. Therefore, investigating point cloud quality assessment (PCQA) is instrumental in facilitating immersive media applications, including virtual reality and augmented reality applications. Considering reference point clouds are not available in many cases, no-reference (NR) metrics have become a research hotspot. Existing NR methods suffer from difficult training. To address this shortcoming, we propose a novel NR-PCQA method, Point Cloud Quality Assessment via Domain-relevance Degradation Description (D3-PCQA). First, we demonstrate our model’s interpretability by deriving the function of each module using a kernelized ridge regression model. Specifically, quality assessment can be characterized as a leap from the scattered perceptual domain (reflecting subjective perception) to the ordered quality domain (reflecting mean opinion score). Second, to reduce the significant domain discrepancy, we establish an intermediate domain, the description domain, based on insights from the human visual system (HVS), by considering the domain relevance among samples located in the perception domain and learning a structured latent space. The anchor features derived from the learned latent space are generated as cross-domain auxiliary information to promote domain transformation. Furthermore, the newly established description domain decomposes the NR-PCQA problem into two relevant stages. These stages include a classification stage that gives the degradation descriptions to point clouds and a regression stage to determine the confidence degrees of descriptions, providing a semantic explanation for the predicted quality scores. Experimental results demonstrate that D3-PCQA exhibits robust performance and outstanding generalization on several publicly available datasets.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 2","pages":"616-630"},"PeriodicalIF":3.2,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exploring Invertible Encoding for Deep Video Compression","authors":"Haifeng Guo;Sam Kwong;Mingliang Zhou","doi":"10.1109/TBC.2025.3541869","DOIUrl":"https://doi.org/10.1109/TBC.2025.3541869","url":null,"abstract":"Deep video compression methods typically use autoencoder-style networks for encoding and decoding, which can result in the loss of information during encoding that cannot be retrieved during decoding. To address this issue, recent work has explored the use of invertible neural networks for enhanced invertible encoding, which has successfully mitigated spatial information loss for better image compression. In this paper, we propose a new approach that extends invertible encoding to temporal information and introduces an encoding-decoding network for deep video compression. Our network incorporates a novel attentive channel squeeze module to improve compression performance while also leveraging a conditional coding framework for motion compression. The entire framework is optimized via a single loss function that balances bit cost and frame quality. The experimental results demonstrate the effectiveness of our approach, which achieves 15.45%/57.92% bit savings in terms of PSNR/MS-SSIM compared with the high-efficiency video coding low-delay P configuration.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 2","pages":"517-528"},"PeriodicalIF":3.2,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10906771","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qian Huang;Xiaoyin Yi;Fei Qi;Lei Liu;Qingming Xie;Qin Jiang;Chunxia Hu
{"title":"Enhancing 5G V2X URLLC Broadcast/Multicast Services With FL-Based Wireless Resource Allocation","authors":"Qian Huang;Xiaoyin Yi;Fei Qi;Lei Liu;Qingming Xie;Qin Jiang;Chunxia Hu","doi":"10.1109/TBC.2025.3541887","DOIUrl":"https://doi.org/10.1109/TBC.2025.3541887","url":null,"abstract":"This paper addresses the challenges of wireless resource allocation for 5G Ultra-reliable Low-latency Communication (URLLC) broadcast/multicast services in Vehicle-to-Everything (V2X) scenarios. It proposes three key algorithms: an iterative resource allocation approach that decomposes optimization into power and spectrum subproblems, a federated learning-based multicast resource allocation scheme that protects data privacy while enabling distributed training, and a cooperative multi-agent reinforcement learning solution that treats vehicles as intelligent nodes to jointly optimize system throughput, URLLC delivery rate, and multicast performance. Path loss models, mobility patterns, and interference scenarios are analyzed for both unicast and multicast transmissions. Simulation results demonstrate that the proposed algorithms achieve superior performance in terms of throughput, reliability, and latency compared to traditional and baseline approaches.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 2","pages":"384-396"},"PeriodicalIF":3.2,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Simplified Fast List PAC Decoder for Broadcasting Services in 6G: Algorithm and Implementation","authors":"Jingxin Dai;Hang Yin;Yansong Lv;Yuhuan Wang;Yin Xu;Rui Lv","doi":"10.1109/TBC.2025.3534624","DOIUrl":"https://doi.org/10.1109/TBC.2025.3534624","url":null,"abstract":"In the 6G network, integrating broadcasting and mobile networks will significantly improve the transmission capability. Considering the excellent error-correction performance, polarized-adjusted convolutional (PAC) codes are promising for ensuring reliable data transmission in 6G broadcasting services. However, the inherent high decoding latency of PAC codes poses challenges for seamless switching between broadcasting and mobile services. In this paper, we propose a simplified fast list (SFL) PAC decoder, which jointly exploits the node thresholds and adaptive path-pruning technology to reduce the decoding latency while maintaining high reliability. Firstly, we present a novel path expansion rule based on the node thresholds to avoid unnecessary computations. Secondly, the introduction of the adaptive path-pruning technology efficiently reduces the number of sorting operations. Moreover, we implement the proposed decoder on general purpose processors (GPPs) by software. Simulation results show that the proposed SFL decoding algorithm significantly reduces the decoding latency by up to 75.18% compared to the state-of-the-art (SOTA) work with no noticeable degradation in error-correction performance. Software implementation of the proposed decoder achieves an 18.80% improvement in throughput performance over the SOTA PAC software decoder.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 2","pages":"397-410"},"PeriodicalIF":3.2,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Heterogeneous Network Transmission Architecture Based on NOMA for Next-Generation Converged Communications and Broadcasting Systems","authors":"Xiaowu Ou;Haoyang Li;Yin Xu;Dazhi He;Wenjun Zhang;Yiyan Wu","doi":"10.1109/TBC.2025.3534620","DOIUrl":"https://doi.org/10.1109/TBC.2025.3534620","url":null,"abstract":"Inter-Tower Communication Network (ITCN), which supports communication between different base stations via wireless links, has excellent potential for simultaneous transmission of broadcast data and personalized data using Layered Division Multiplexing (LDM). In this paper, a heterogeneous ITCN architecture using LDM and wireless backhauling is proposed. In uplink transmission, the power-limited user devices transmit data to the secondary transmitters (STs), and the STs relay the data to the master transmitter (MT). In downlink transmission, the MT and multiple STs cooperatively transmit broadcast data using single frequency network (SFN) mode, and the STs relay the personalized data from the MT to users simultaneously. Considering the co-channel interference, this paper proposes a joint subchannel assignment and power allocation scheme for both uplink and downlink transmission. A mixed integer optimization problem is formulated, and an alternating optimization algorithm (AO) based on game theory and convex optimization is proposed. Simulation results are conducted with different system configurations to demonstrate the convergence and effectiveness of the proposed algorithms.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 2","pages":"372-383"},"PeriodicalIF":3.2,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-Level Perception Assessment for Underwater Image Enhancement","authors":"Yiwen Xu;Yuxiang Lin;Nian He;Xuejin Wang;Tiesong Zhao","doi":"10.1109/TBC.2025.3525972","DOIUrl":"https://doi.org/10.1109/TBC.2025.3525972","url":null,"abstract":"Due to the complex underwater imaging environment, existing Underwater Image Enhancement (UIE) techniques are unable to handle the increasing demand for high-quality underwater content in broadcasting systems. Thus, a robust quality assessment method is highly expected to effectively compare the quality of different enhanced underwater images. To this end, we propose a novel quality assessment method for enhanced underwater images by utilizing multiple levels of features at various stages of the network’s depth. We first select underwater images with different distortions to analyze the characteristics of different UIE results at various feature levels. We found that low-level features are more sensitive to color information, while mid-level features are more indicative of structural differences. Based on this, a Channel-Spatial-Pixel Attention Module (CSPAM) is designed for low-level perception to capture color characteristics, utilizing channel, spatial, and pixel dimensions. To capture structural variations, a Parallel Structural Perception Module (PSPM) with convolutional kernels of different scales is introduced for mid-level perception. For high-level perception, due to the accumulation of noise, an Adaptive Weighted Downsampling (AWD) layer is employed to restore the semantic information. Furthermore, a new top-down multi-level feature fusion method is designed. Information from different levels is integrated through a Selective Feature Fusion (SFF) mechanism, which produces semantically rich features and enhances the model’s feature representation capability. Experimental results demonstrate the superior performance of the proposed method over the competing image quality evaluation methods.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 2","pages":"606-615"},"PeriodicalIF":3.2,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cross-Domain Feature Interaction Network for Stereo Image Quality Assessment Considering Difference Information Guiding Binocular Fusion","authors":"Yongli Chang;Guanghui Yue;Bo Zhao","doi":"10.1109/TBC.2025.3525976","DOIUrl":"https://doi.org/10.1109/TBC.2025.3525976","url":null,"abstract":"Recently, convolutional neural network (CNN) based stereo image quality assessment (SIQA) has been extensively researched, achieving impressive performance. However, most SIQA methods tend to only mine features from distorted stereo image, neglecting the exploitation of valuable features present in other image domains. Moreover, some simple fusion strategies like addition and concatenation for binocular fusion further limit the network’s prediction performance. Therefore, we design a cross-domain feature interaction network (CDFINet) for SIQA in this paper, which considers the complementarity between different domain features and realizes binocular fusion between the left and right monocular features based on difference information. Specifically, to boost the prediction ability, we design a dual-branch network with image and gradient feature extraction branches, extracting hierarchical features from both domains. Moreover, to explore more proper binocular information, we propose a difference information guidance based binocular fusion (DIGBF) module to achieve the binocular fusion. Furthermore, to better achieve information compensation between image and gradient domain, binocular features obtained from image domain and gradient domain are fused in the proposed cross-domain feature fusion (CDFF) module. In addition, considering the feedback mechanism of the visual cortex, higher-level features are backpropagated to lower-level regions, and the proposed cross-layer feature interaction (CLFI) module realizes the guidance of higher-level features to lower-level features. Finally, to encourage a more effective way to get the perceptual quality, a hierarchical multi-score quality aggregation method is proposed. The experimental results on four SIQA databases show that our CDFINet outperforms the compared mainstream metrics.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 2","pages":"593-605"},"PeriodicalIF":3.2,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hongwei Guo;Ce Zhu;Junjie Chen;Lei Luo;Yongkai Huo;Yutian Liu
{"title":"Distortion Propagation Factor Estimation for VVC Low-Delay Hierarchical Coding","authors":"Hongwei Guo;Ce Zhu;Junjie Chen;Lei Luo;Yongkai Huo;Yutian Liu","doi":"10.1109/TBC.2024.3519909","DOIUrl":"https://doi.org/10.1109/TBC.2024.3519909","url":null,"abstract":"Previous studies have shown that temporally dependent rate-distortion optimization (RDO) methods can enhance the compression performance of video encoders. However, accurately quantifying temporal rate-distortion dependencies in the latest video coding standard, Versatile Video Coding (VVC), remains a significant challenge. To address this issue, this paper proposes a distortion propagation factor (DPF) estimation method tailored for VVC low-delay hierarchical coding, aiming to achieve temporally dependent RDO. Specifically, we first derive a formula for calculating the DPF based on coding distortion and motion-compensated prediction (MCP) errors. Building on this, we present several pre-encoding-based DPF estimation schemes designed for the VVC low-delay hierarchical coding structure. These schemes have very low computational complexity and do not require buffering subsequent unencoded frames for pre-analysis, thereby avoiding additional encoding delays. Finally, the estimated DPFs are used to adaptively adjust the Lagrange multipliers and quantization parameters of each coding tree unit, optimizing the allocation of coding bit resources. After integrating the proposed method into the VVC test model VTM-23.0, experimental results show that one of the proposed DPF estimation schemes achieves average bit rate savings of 4.25% for low-delay B slices and 4.12% for low-delay P slices, with only a 1% increase in computational complexity. The proposed method offers an effective solution for enhancing the compression performance of VVC encoders. Consequently, the proposed DPF estimation approaches have already been adopted by the Joint Video Experts Team (JVET) and officially integrated into the VVC reference software.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 2","pages":"492-505"},"PeriodicalIF":3.2,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Allan Seiti Sassaqui Chaubet;Rodrigo Admir Vaz;George Henrique Maranhão Garcia de Oliveira;Ricardo Seriacopi Rabaça;Isabela Coelho Dourado;Gustavo de Melo Valeira;Cristiano Akamine
{"title":"TV 3.0: An Overview","authors":"Allan Seiti Sassaqui Chaubet;Rodrigo Admir Vaz;George Henrique Maranhão Garcia de Oliveira;Ricardo Seriacopi Rabaça;Isabela Coelho Dourado;Gustavo de Melo Valeira;Cristiano Akamine","doi":"10.1109/TBC.2024.3511928","DOIUrl":"https://doi.org/10.1109/TBC.2024.3511928","url":null,"abstract":"A new Digital Terrestrial Television Broadcasting (DTTB) system, called Television (TV) 3.0, is being developed in Brazil and is expected to be on air by 2025 under the commercial name DTV+. It started with a Call for Proposals (CfP) for its systems components, for which organizations worldwide have submitted candidate technologies. After two testing and evaluation phases, the technologies for all layers were selected, the TV 3.0 architecture was completely defined, and the standards were written. It consists of modern Modulation and Code (MODCOD) techniques, mandatory transmission and reception in Multiple-Input Multiple-Output (MIMO) with cross-polarized antennas, an app-oriented interface, an Internet-based Transport Layer (TL), and state-of-the-art efficient coding for audio, video, and captions. This set of technologies will allow for several new use cases that change the user experience with TV, such as Geographically Segmented Broadcasting (GSB), targeted advertising, sensory effects, and interactivity. This paper reviews the phases already concluded for the TV 3.0 project and presents its potentialities and the current developments at its final stage.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 1","pages":"11-18"},"PeriodicalIF":3.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Digital Entity Management Methodology for Digital Twin Implementation: Concept, Definition, and Examples","authors":"Yegi Lee;Myung-Sun Baek;Kyoungro Yoon","doi":"10.1109/TBC.2024.3517138","DOIUrl":"https://doi.org/10.1109/TBC.2024.3517138","url":null,"abstract":"Many efforts to achieve cost savings through simulations have been ongoing in the cyber-physical system (CPS) industry and manufacturing field. Recently, the concept of digital twins has emerged as a promising solution for cost reduction in various fields, such as smart cities, factory optimization, architecture, and manufacturing. Digital twins offer enormous potential by continuously monitoring and updating data to study a wide range of issues and improve products and processes. However, the practical implementation of digital twins presents significant challenges. Additionally, while various studies have introduced the concepts and roles of digital twin systems and digital components, further research is needed to explore efficient operation and management strategies. This paper aims to present digital entity management methodology for the efficient implementation of digital twin systems. Our proposed class-level digital entity management methodology constructs complex and repetitively used digital entities into digital entity classes. This approach facilitates the abstraction, inheritance, and upcasting of digital entity classes. By leveraging class-level management and easily reusable and modifiable digital entities, the implementation of low-complexity digital twin systems becomes feasible. The proposed methodology aims to streamline the digital twin implementation process, addressing complex technical integration and practical implementation challenges.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 1","pages":"19-29"},"PeriodicalIF":3.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}