Video transcoding is to create multiple representations of a video for content adaptation.It is deemed as a core technique in Adaptive BitRate(ABR)streaming.How to manage video transcoding affects the performance of A...Video transcoding is to create multiple representations of a video for content adaptation.It is deemed as a core technique in Adaptive BitRate(ABR)streaming.How to manage video transcoding affects the performance of ABR streaming in various aspects,including operational cost,streaming delays,Quality of Experience(QoE),etc.Therefore,the problems of implementing video transcoding in ABR streaming must be systematically studied to improve the overall performance of the streaming services.These problems become more worthy of investigation with the emergence of the edge-cloud continuum,which makes the resource allocation for video transcoding more complicated.To this end,this paper provides an investigation of the main technical problems related to video transcoding in ABR streaming,including designing a rate profile for video transcoding,providing resources for video transcoding in clouds,and caching multi-bitrate video contents in networks,etc.We analyze these problems from the perspective of resource allocation in the edge-cloud continuum and cast them into resource and Quality of Service(QoS)optimization problems.The goal is to minimize resource consumption while guaranteeing the QoS for ABR streaming.We also discuss some promising research directions for the ABR streaming services.展开更多
A content-aware multi-step prediction control(CAMPC)algorithm is proposed to determine the bitrate of 360-degree videos,aim⁃ing to enhance the quality of experience(QoE)of users and reduce the cost of video content pr...A content-aware multi-step prediction control(CAMPC)algorithm is proposed to determine the bitrate of 360-degree videos,aim⁃ing to enhance the quality of experience(QoE)of users and reduce the cost of video content providers(VCP).The CAMPC algorithm first em⁃ploys a neural network to generate the content richness and combines it with the current field of view(FOV)to accurately predict the probability distribution of tiles being viewed.Then,for the tiles in the predicted viewport which directly affect QoE,the CAMPC algorithm utilizes a multi-step prediction for future system states,and accordingly selects the bitrates of multiple subsequent steps,instead of an instantaneous state.Meanwhile,it controls the buffer occupancy to eliminate the impact of prediction errors.We implement CAMPC on players by building a 360-degree video streaming platform and evaluating other advanced adaptive bitrate(ABR)rules through the real network.Experimental results show that CAMPC can save 83.5%of bandwidth resources compared with the scheme that completely transmits the tiles outside the viewport with the Dynamic Adaptive Streaming over HTTP(DASH)protocol.Besides,the proposed method can improve the system utility by 62.7%and 27.6%compared with the DASH official and viewport-based rules,respectively.展开更多
Dynamic adaptive streaming over HTTP(DASH)can adaptively select the appropriate video bitrate for mobile users.Mobile edge computing(MEC)scenario is of great benefit to improve the performance of mobile networks by pr...Dynamic adaptive streaming over HTTP(DASH)can adaptively select the appropriate video bitrate for mobile users.Mobile edge computing(MEC)scenario is of great benefit to improve the performance of mobile networks by providing computing and storage capabilities.And the utilization of spectrum resources can be improved by multicast transmission,but the performance of the multicast transmission will be directly affected by the selected grouping algorithm and resource allocation algorithm.In order to improve the quality of experience(QoE)of video users in the 5G MEC scenario,this paper proposes a QoE-driven DASH multicast scheme,which mainly covers the grouping algorithm and the adaptive bitrate(ABR)algorithm.First of all,we take the optimized target QoE as the basis for grouping and propose an adaptive grouping algorithm that can dynamically adjust the grouping results.Besides,we design a joint optimization ABR algorithm based on the prediction of QoE,which comprehensively considers the process of resource allocation and bitrate decision-making based on the prediction of QoE of video segments in a certain forward-looking field of view.The simulation results show that the proposed DASH multicast scheme performs well in QoE and fairness.展开更多
In the procedure of encoding process on low bitrate speech,fixed codebook division is an efficient and promising embedding method for steganography.An improved neighbor index division(NID)steganography method based on...In the procedure of encoding process on low bitrate speech,fixed codebook division is an efficient and promising embedding method for steganography.An improved neighbor index division(NID)steganography method based on the high bitrate frame of G.723.1 codec(6.3kbit/s)is proposed,which employs the parity and low distortion of neighbor indices for G.723.1 fixed codebooks.Differing from previously NID method which performs quantized index modulation(QIM)beforehand,the proposed method divides codeword indices into separate sub-codebooks according to the secret message bits dynamically in the original G.723.1 codec quantization period.Compared with existing NID method,our proposed method doesn’t need to divide the codebook before the encoding starts.The embedding and codebook dividing happen simultaneously,which utilizes the characteristics of specific secret message bits.The experiment results show that the proposed method has a much lower quality degradation for the decoding speech and still fulfills the low latency requirement for communication.展开更多
With the expansive demand for video streaming over mobile networks,it is necessary to adopt schemes that balance the need for high video quality with the available network resources when streaming or downloading the v...With the expansive demand for video streaming over mobile networks,it is necessary to adopt schemes that balance the need for high video quality with the available network resources when streaming or downloading the video.Several approaches were proposed in the literature,including Dynamic Adaptive Streaming over HTTP(DASH).In this work,we consider an approach in which we place sufficient emphasis on the constrained battery resources in mobile devices when making decisions on the quality(or bitrate)of the video to be requested.This is done by using a fuzzy logic controller that enhances the performance of the Fuzzy-based DASH(FDASH)scheme.Simulation results show that our proposed approach conserves more energy than its predecessor while maintaining similar video quality and avoiding playback interruptions.展开更多
In-loop filtering significantly helps detect and remove blocking artifacts across block boundaries in low bitrate coded High Efficiency Video Coding(HEVC)frames and improves its subjective visual quality in multimedia...In-loop filtering significantly helps detect and remove blocking artifacts across block boundaries in low bitrate coded High Efficiency Video Coding(HEVC)frames and improves its subjective visual quality in multimedia services over communication networks.However,on faster processing of the complex videos at a low bitrate,some visible artifacts considerably degrade the picture quality.In this paper,we proposed a four-step fuzzy based adaptive deblocking filter selection technique.The proposed method removes the quantization noise,blocking artifacts and corner outliers efficiently for HEVC coded videos even at low bit-rate.We have considered Y(luma),U(chromablue),and V(chroma-red)components parallelly.Finally,we have developed a fuzzy system to detect blocking artifacts and use adaptive filters as per requirement in all four quadrants,namely up 45◦,down 45◦,up 135◦,and down 135◦across horizontal and vertical block boundaries.In this context,experimentation is done on a wide variety of videos.An objective and subjective analysis is carried out with MATLAB software and Human Visual System(HVS).The proposed method substantially outperforms existing postprocessing deblocking techniques in terms of YPSNR and BD_rate.In the proposed method,we achieved 0.32–0.97 dB values of YPSNR.Our method achieved a BD_rate of+1.69%for the luma component,−0.18%(U)and−1.99%(V)for chroma components,respectively,with respect to the stateof-the-art methods.The proposed method proves to have low computational complexity and has better parallel processing,hence suitable for a real-time system in the near future.展开更多
为了保证一定视频质量下编码器输出的码率符合给定的目标码率,提出一种考虑视频内容特性的H.265/HEVC帧层码率分配算法。首先从率失真理论分析的角度推导出影响输出码率的主要因素,然后根据视频编码原理,预测出帧内容复杂度参数,从而建...为了保证一定视频质量下编码器输出的码率符合给定的目标码率,提出一种考虑视频内容特性的H.265/HEVC帧层码率分配算法。首先从率失真理论分析的角度推导出影响输出码率的主要因素,然后根据视频编码原理,预测出帧内容复杂度参数,从而建立一种更有效的帧层码率分配算法。实验结果表明,所提算法可以使帧层目标码率与编码码率保持更好的一致性,且重构视频质量平均提高了0.103 d B。展开更多
基金supported in part by the Natural Science Foundation of Jiangsu Province under Grant BK20200486.
文摘Video transcoding is to create multiple representations of a video for content adaptation.It is deemed as a core technique in Adaptive BitRate(ABR)streaming.How to manage video transcoding affects the performance of ABR streaming in various aspects,including operational cost,streaming delays,Quality of Experience(QoE),etc.Therefore,the problems of implementing video transcoding in ABR streaming must be systematically studied to improve the overall performance of the streaming services.These problems become more worthy of investigation with the emergence of the edge-cloud continuum,which makes the resource allocation for video transcoding more complicated.To this end,this paper provides an investigation of the main technical problems related to video transcoding in ABR streaming,including designing a rate profile for video transcoding,providing resources for video transcoding in clouds,and caching multi-bitrate video contents in networks,etc.We analyze these problems from the perspective of resource allocation in the edge-cloud continuum and cast them into resource and Quality of Service(QoS)optimization problems.The goal is to minimize resource consumption while guaranteeing the QoS for ABR streaming.We also discuss some promising research directions for the ABR streaming services.
基金supported in part by ZTE Corporation under Grant No.2021420118000065.
文摘A content-aware multi-step prediction control(CAMPC)algorithm is proposed to determine the bitrate of 360-degree videos,aim⁃ing to enhance the quality of experience(QoE)of users and reduce the cost of video content providers(VCP).The CAMPC algorithm first em⁃ploys a neural network to generate the content richness and combines it with the current field of view(FOV)to accurately predict the probability distribution of tiles being viewed.Then,for the tiles in the predicted viewport which directly affect QoE,the CAMPC algorithm utilizes a multi-step prediction for future system states,and accordingly selects the bitrates of multiple subsequent steps,instead of an instantaneous state.Meanwhile,it controls the buffer occupancy to eliminate the impact of prediction errors.We implement CAMPC on players by building a 360-degree video streaming platform and evaluating other advanced adaptive bitrate(ABR)rules through the real network.Experimental results show that CAMPC can save 83.5%of bandwidth resources compared with the scheme that completely transmits the tiles outside the viewport with the Dynamic Adaptive Streaming over HTTP(DASH)protocol.Besides,the proposed method can improve the system utility by 62.7%and 27.6%compared with the DASH official and viewport-based rules,respectively.
基金the National Key R&D Program of China under Grant 2020YFA0711400the National Science Foundation of China under Grant 61673360the CETC Joint Advanced Research Foundation under Grant 6141B08080101.
文摘Dynamic adaptive streaming over HTTP(DASH)can adaptively select the appropriate video bitrate for mobile users.Mobile edge computing(MEC)scenario is of great benefit to improve the performance of mobile networks by providing computing and storage capabilities.And the utilization of spectrum resources can be improved by multicast transmission,but the performance of the multicast transmission will be directly affected by the selected grouping algorithm and resource allocation algorithm.In order to improve the quality of experience(QoE)of video users in the 5G MEC scenario,this paper proposes a QoE-driven DASH multicast scheme,which mainly covers the grouping algorithm and the adaptive bitrate(ABR)algorithm.First of all,we take the optimized target QoE as the basis for grouping and propose an adaptive grouping algorithm that can dynamically adjust the grouping results.Besides,we design a joint optimization ABR algorithm based on the prediction of QoE,which comprehensively considers the process of resource allocation and bitrate decision-making based on the prediction of QoE of video segments in a certain forward-looking field of view.The simulation results show that the proposed DASH multicast scheme performs well in QoE and fairness.
基金This work is supported in part by the First Batch of Youth Innovation Fund Projects in 2020 under Grant No.3502Z202006012 and the Experimental Teaching Reform Project of National Huaqiao University under Grant No.SY2019L013.
文摘In the procedure of encoding process on low bitrate speech,fixed codebook division is an efficient and promising embedding method for steganography.An improved neighbor index division(NID)steganography method based on the high bitrate frame of G.723.1 codec(6.3kbit/s)is proposed,which employs the parity and low distortion of neighbor indices for G.723.1 fixed codebooks.Differing from previously NID method which performs quantized index modulation(QIM)beforehand,the proposed method divides codeword indices into separate sub-codebooks according to the secret message bits dynamically in the original G.723.1 codec quantization period.Compared with existing NID method,our proposed method doesn’t need to divide the codebook before the encoding starts.The embedding and codebook dividing happen simultaneously,which utilizes the characteristics of specific secret message bits.The experiment results show that the proposed method has a much lower quality degradation for the decoding speech and still fulfills the low latency requirement for communication.
文摘With the expansive demand for video streaming over mobile networks,it is necessary to adopt schemes that balance the need for high video quality with the available network resources when streaming or downloading the video.Several approaches were proposed in the literature,including Dynamic Adaptive Streaming over HTTP(DASH).In this work,we consider an approach in which we place sufficient emphasis on the constrained battery resources in mobile devices when making decisions on the quality(or bitrate)of the video to be requested.This is done by using a fuzzy logic controller that enhances the performance of the Fuzzy-based DASH(FDASH)scheme.Simulation results show that our proposed approach conserves more energy than its predecessor while maintaining similar video quality and avoiding playback interruptions.
文摘In-loop filtering significantly helps detect and remove blocking artifacts across block boundaries in low bitrate coded High Efficiency Video Coding(HEVC)frames and improves its subjective visual quality in multimedia services over communication networks.However,on faster processing of the complex videos at a low bitrate,some visible artifacts considerably degrade the picture quality.In this paper,we proposed a four-step fuzzy based adaptive deblocking filter selection technique.The proposed method removes the quantization noise,blocking artifacts and corner outliers efficiently for HEVC coded videos even at low bit-rate.We have considered Y(luma),U(chromablue),and V(chroma-red)components parallelly.Finally,we have developed a fuzzy system to detect blocking artifacts and use adaptive filters as per requirement in all four quadrants,namely up 45◦,down 45◦,up 135◦,and down 135◦across horizontal and vertical block boundaries.In this context,experimentation is done on a wide variety of videos.An objective and subjective analysis is carried out with MATLAB software and Human Visual System(HVS).The proposed method substantially outperforms existing postprocessing deblocking techniques in terms of YPSNR and BD_rate.In the proposed method,we achieved 0.32–0.97 dB values of YPSNR.Our method achieved a BD_rate of+1.69%for the luma component,−0.18%(U)and−1.99%(V)for chroma components,respectively,with respect to the stateof-the-art methods.The proposed method proves to have low computational complexity and has better parallel processing,hence suitable for a real-time system in the near future.
文摘为了保证一定视频质量下编码器输出的码率符合给定的目标码率,提出一种考虑视频内容特性的H.265/HEVC帧层码率分配算法。首先从率失真理论分析的角度推导出影响输出码率的主要因素,然后根据视频编码原理,预测出帧内容复杂度参数,从而建立一种更有效的帧层码率分配算法。实验结果表明,所提算法可以使帧层目标码率与编码码率保持更好的一致性,且重构视频质量平均提高了0.103 d B。
