IEEE Transactions on Broadcasting最新文献_第6页

Spatial Coupling Strategy and Improved BFGS-Based Advanced Rate Control for VVC 空间耦合策略及基于改进bfgs的VVC高级速率控制

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2024-12-31 DOI: 10.1109/TBC.2024.3517167

Jiahao Zhang;Shuhua Xiong;Xiaohai He;Zeming Zhao;Hongdong Qin

{"title":"Spatial Coupling Strategy and Improved BFGS-Based Advanced Rate Control for VVC","authors":"Jiahao Zhang;Shuhua Xiong;Xiaohai He;Zeming Zhao;Hongdong Qin","doi":"10.1109/TBC.2024.3517167","DOIUrl":"https://doi.org/10.1109/TBC.2024.3517167","url":null,"abstract":"This paper presents an advanced rate control (ARC) algorithm for Versatile Video Coding (VVC). The proposed method is based on spatial coupling strategy and improved Broyden Fletcher Goldfarb Shanno (BFGS) algorithm to achieve a high performance rate control (RC). In this paper, we address the problem that the current coding block does not fully utilise the spatial information during the encoding process. Firstly, a parameter updating strategy at the coding tree unit (CTU) level is constructed based on spatial coupling strategy. The spatial coupling strategy established the relationship between video parameters and video texture, which enables the video parameters at the CTU level to be more closely aligned with the video content. Furthermore, in order to enhance the precision of RC, we have proposed an improved BFGS algorithm to update video parameters, which utilizes the optimal search direction of the different partial differentials and sets an adaptive speed control factor. The experimental results indicate that the proposed method offers better performance compared to the default RC in VVC Test Moder (VTM) 19.0, with Bjøntegaard Delta Rate (BD-Rate) savings of 6.35%, 5.09% and 5.43% under Low Delay P, Low Delay B and Random Access configurations, respectively. Moreover, the proposed method demonstrates superior performance compared to other state-of-the-art algorithms.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 1","pages":"111-124"},"PeriodicalIF":3.2,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553464","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}

引用次数: 0

Generalizable Underwater Image Quality Assessment With Curriculum Learning-Inspired Domain Adaption 基于课程学习启发域自适应的广义水下图像质量评价

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2024-12-27 DOI: 10.1109/TBC.2024.3511962

Shihui Wu;Qiuping Jiang;Guanghui Yue;Shiqi Wang;Guangtao Zhai

{"title":"Generalizable Underwater Image Quality Assessment With Curriculum Learning-Inspired Domain Adaption","authors":"Shihui Wu;Qiuping Jiang;Guanghui Yue;Shiqi Wang;Guangtao Zhai","doi":"10.1109/TBC.2024.3511962","DOIUrl":"https://doi.org/10.1109/TBC.2024.3511962","url":null,"abstract":"The complex distortions suffered by real-world underwater images pose urgent demands on accurate underwater image quality assessment (UIQA) approaches that can predict underwater image quality consistently with human perception. Deep learning techniques have achieved great success in many applications, yet usually requiring a substantial amount of human-labeled data, which is time-consuming and labor-intensive. Developing a deep learning-based UIQA method that does not rely on any human labeled underwater images for model training poses a great challenge. In this work, we propose a novel UIQA method based on domain adaption (DA) from a curriculum learning perspective. The proposed method is called curriculum learning-inspired DA (CLIDA), aiming to learn an robust and generalizable UIQA model by conducting DA between the labeled natural images and unlabeled underwater images progressively, i.e., from easy to hard. The key is how to select easy samples from all underwater images in the target domain so that the difficulty of DA can be well-controlled at each stage. To this end, we propose a simple yet effective easy sample selection (ESS) scheme to form an easy sample set at each stage. Then, DA is performed between the entire natural image set in the source domain (with labels) and the selected easy sample set in the target domain (with pseudo labels) at each stage. As only those reliable easy examples are involved in DA at each stage, the difficulty of DA is well-controlled and the capability of the model is expected to be progressively enhanced. We conduct extensive experiments to verify the superiority of the proposed CLIDA method and also the effectiveness of each key component involved in our CLIDA framework. The source code will be made available at <uri>https://github.com/zzeu001/CLIDA</uri>.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 1","pages":"252-263"},"PeriodicalIF":3.2,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553155","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}

引用次数: 0

CLIPVQA: Video Quality Assessment via CLIP CLIPVQA：视频质量评估通过剪辑

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2024-12-27 DOI: 10.1109/TBC.2024.3511927

Fengchuang Xing;Mingjie Li;Yuan-Gen Wang;Guopu Zhu;Xiaochun Cao

{"title":"CLIPVQA: Video Quality Assessment via CLIP","authors":"Fengchuang Xing;Mingjie Li;Yuan-Gen Wang;Guopu Zhu;Xiaochun Cao","doi":"10.1109/TBC.2024.3511927","DOIUrl":"https://doi.org/10.1109/TBC.2024.3511927","url":null,"abstract":"In learning vision-language representations from Web-scale data, the contrastive language-image pre-training (CLIP) mechanism has demonstrated a remarkable performance in many vision tasks. However, its application to the widely studied video quality assessment (VQA) task is still an open issue. In this paper, we propose an efficient and effective CLIP-based Transformer method for the VQA problem (CLIPVQA). Specifically, we first design an effective video frame perception paradigm with the goal of extracting the rich spatiotemporal quality and content information among video frames. Then, the spatiotemporal quality features are adequately integrated together using a self-attention mechanism to yield video-level quality representation. To utilize the quality language descriptions of videos for supervision, we develop a CLIP-based encoder for language embedding, which is then fully aggregated with the generated content information via a cross-attention module for producing video-language representation. Finally, the video-level quality and video-language representations are fused together for final video quality prediction, where a vectorized regression loss is employed for efficient end-to-end optimization. Comprehensive experiments are conducted on eight in-the-wild video datasets with diverse resolutions to evaluate the performance of CLIPVQA. The experimental results show that the proposed CLIPVQA achieves new state-of-the-art VQA performance and up to 37% better generalizability than existing benchmark VQA methods. A series of ablation studies are also performed to validate the effectiveness of each module in CLIPVQA.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 1","pages":"291-306"},"PeriodicalIF":3.2,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553314","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}

引用次数: 0

Joint Optimization of Beamforming and Subarray Assignment for Full-Duplex Arrays in Next Generation Broadcast Systems 下一代广播系统中全双工阵列波束形成与子阵列分配的联合优化

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2024-12-25 DOI: 10.1109/TBC.2024.3517141

Lang Lin;Wensheng Pan;Hongzhi Zhao;Shengfeng Zhang;Shihai Shao;Youxi Tang

{"title":"Joint Optimization of Beamforming and Subarray Assignment for Full-Duplex Arrays in Next Generation Broadcast Systems","authors":"Lang Lin;Wensheng Pan;Hongzhi Zhao;Shengfeng Zhang;Shihai Shao;Youxi Tang","doi":"10.1109/TBC.2024.3517141","DOIUrl":"https://doi.org/10.1109/TBC.2024.3517141","url":null,"abstract":"The full-duplex (FD) technique provides spectrum-efficient transmission service by supporting uplink and downlink transmission at the same time over the same frequency band. Combined FD with multi-input multi-output (MIMO) antenna systems can improve the capability and efficiency of next-generation broadcasting to provide various services for multiple users. However, the strong self-interference (SI) coupled between the transmit and receive arrays is a significant challenge for simultaneous transmission and reception. This study considers multi-user oriented broadcast systems where the transmit array with subarray division allows simultaneous multi-beam transmission. Our objective is to mitigate SI from two aspects: 1) subarray assignment; 2) adaptive transmit beamforming (TxBF). We propose a min-SI TxBF design jointly with subarray assignment, which determines the best subarray assignment pattern and provides a closed-form solution of the optimal TxBF weight. Theoretical analysis and simulations show our design has a low algorithm complexity. Based on the measured SI channel data collected from a hardware prototype testbed, simulation results verify that the min-SI TxBF design with subarray assignment can effectively enhance SI cancelation.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 2","pages":"672-679"},"PeriodicalIF":3.2,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243909","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}

引用次数: 0

Distortion Propagation Model-Based V-PCC Rate Control for 3D Point Cloud Broadcasting 基于失真传播模型的三维点云广播V-PCC速率控制

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2024-12-12 DOI: 10.1109/TBC.2024.3511950

Zhanyuan Cai;Wenxu Gao;Ge Li;Wei Gao

{"title":"Distortion Propagation Model-Based V-PCC Rate Control for 3D Point Cloud Broadcasting","authors":"Zhanyuan Cai;Wenxu Gao;Ge Li;Wei Gao","doi":"10.1109/TBC.2024.3511950","DOIUrl":"https://doi.org/10.1109/TBC.2024.3511950","url":null,"abstract":"For efficient point cloud broadcasting, point cloud compression technologies serve as the foundation, which plays a crucial role in immersive media communication and streaming. Video-based point cloud compression (V-PCC) is the recently developed standard by the Moving Picture Experts Group (MPEG) for dynamic point clouds. Its original fixed-ratio bit allocation (FR-BA) method in the unique all intra (AI) structure leads to a significant rate-distortion performance gap between the rate control manner and the fixed quantization parameters (FixedQP) scheme, as evidenced by significant increases in BD-Rate (Bjøntegaard Delta Rate) for both geometry and attribute. To address this issue, we propose a distortion propagation model-based frame-level bit allocation method that is specifically tailored for AI structure in V-PCC. First, the analysis is carried out for the distortion propagation model inside the group of pictures (GOP) for the AI configuration. Second, the skip ratio of 4x4 minimum coding units (CUs) is utilized to predict the distortion propagation factor. Third, the occupancy information is employed to refine the distortion propagation model and further enhance compression performance. Finally, experimental results demonstrate the effectiveness of the proposed distortion propagation model-based frame-level bit allocation method. Specifically, experimental results reveal that the proposed method achieves BD-Rate reductions of 0.92% and 4.85% in geometry and attribute, respectively, compared to the FR-BA method. Furthermore, with the introduction of distortion propagation factor prediction incorporating occupancy correction, the BD-Rate reductions are further extended to 2.16% and 6.13% in geometry and attribute, respectively.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 1","pages":"180-192"},"PeriodicalIF":3.2,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553315","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}

引用次数: 0

Rate-Compatible Length-Scalable Quasi-Cyclic Spatially-Coupled LDPC Codes 速率兼容的长度可伸缩准循环空间耦合LDPC码

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2024-12-12 DOI: 10.1109/TBC.2024.3511916

Zhitong He;Kewu Peng;Jian Song

引用次数: 0

IEEE Transactions on Broadcasting Publication Information IEEE广播出版信息汇刊

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2024-12-11 DOI: 10.1109/TBC.2024.3495315

引用次数: 0

2024 Scott Helt Memorial Award for the Best Paper Published in the IEEE Transactions on Broadcasting 2024年斯科特·海尔特纪念奖，在IEEE广播事务中发表的最佳论文

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2024-12-11 DOI: 10.1109/TBC.2024.3492772

引用次数: 0

IEEE Transactions on Broadcasting Information for Authors IEEE作者广播信息汇刊

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2024-12-11 DOI: 10.1109/TBC.2024.3495317

引用次数: 0

Omnidirectional Image Quality Assessment With Mutual Distillation 基于互蒸馏的全方位图像质量评价

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2024-12-03 DOI: 10.1109/TBC.2024.3503435

Pingchuan Ma;Lixiong Liu;Chengzhi Xiao;Dong Xu

{"title":"Omnidirectional Image Quality Assessment With Mutual Distillation","authors":"Pingchuan Ma;Lixiong Liu;Chengzhi Xiao;Dong Xu","doi":"10.1109/TBC.2024.3503435","DOIUrl":"https://doi.org/10.1109/TBC.2024.3503435","url":null,"abstract":"There exists complementary relationship between different projection formats of omnidirectional images. However, most existing omnidirectional image quality assessment (OIQA) works only operate solely on single projection format, and rarely explore the solutions on different projection formats. To this end, we propose a mutual distillation-based omnidirectional image quality assessment method, abbreviated as MD-OIQA. The MD-OIQA explores the complementary relationship between different projection formats to improve the feature representation of omnidirectional images for quality prediction. Specifically, we separately feed equirectangular projection (ERP) and cubemap projection (CMP) images into two peer student networks to capture quality-aware features of specific projection contents. Meanwhile, we propose a self-adaptive mutual distillation module (SAMDM) that deploys mutual distillation at multiple network stages to achieve the mutual learning between the two networks. The proposed SAMDM is able to capture the useful knowledge from the dynamic optimized networks to improve the effect of mutual distillation by enhancing the feature interactions through a deep cross network and generating masks to efficiently capture the complementary information from different projection contents. Finally, the features extracted from single projection content are used for quality prediction. The experiment results on three public databases demonstrate that the proposed method can efficiently improve the model representation capability and achieves superior performance.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 1","pages":"264-276"},"PeriodicalIF":3.2,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553219","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}

引用次数: 0