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Joint Layer Prediction for Improving SHVC Compression Performance and Error Concealment
Dr. Hoang Van Xiem, UET, VNU
Time: 15:30, Tuesday, February 19, 2019
Venue: E3-707, 144 Xuan Thuy, Cau Giay, Hanoi
Scalable High Efficiency Video Coding (SHVC) standard is expected to play a more important role in the heterogeneous landscape of broadcasting, multimedia, networks, and various services applications as it is specified as a layered coding technique in the ATSC (Advanced Television Systems Committee) 3.0. However, its block-based structure of temporal and spatial prediction makes it sensitive to information loss and error propagation due to transmission errors. In this context, we propose an improved SHVC with a joint layer prediction (JLP) solution which adaptively combines the decoded information from the base and the enhancement layers to create an additional reference for the SHVC enhancement encoder. To optimize the quality of the joint prediction, the minimum mean square error (MMSE) estimation is executed in computing a combination factor that gives weights to each contribution of the decoded information from the layers. In addition, the proposed JLP is integrated into the SHVC decoder to work as an error concealment solution to mitigate the error propagation happening inevitably in practical video transmission. Experiments have shown that the proposed SHVC framework significantly outperforms its relevant benchmarks, notably by up to 14.8% in bitrate reduction with respect to the standard SHVC codec. The proposed SHVC error concealment strategy also greatly improves the concealed picture quality as well as reducing the problem of error propagation when compared to conventional error concealment approaches.
Hoang Van Xiem is a member of the Faculty of Electronics and Telecommunications, Vietnam National University – University of Engineering and Technology (VNU-UET). He received the Ph.D. degree (with Distinction) from Lisbon University, Portugal, in 2015, the M.Sc. degree from Sungkyunkwan University, South Korea, in 2011, and the B.E degree from Hanoi University of Science and Technology, Vietnam, in 2009, all in Electrical and Computer Engineering. He is an executive committee member of the VNU-UTS Joint Innovation and Technology research center. His research interests are machine learning, image, video processing, and robot vision. Dr. Xiem has published more than 40 papers on image and video coding and regularly reviews for many renowned IEEE, IET and EURASIP journals, including IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Image Processing, and IEEE Transactions on Broadcasting. He also serves as a technical committee member for many international conferences and funding agencies worldwide. He has received several technical awards for his contributions on image and video coding, including the Best paper award of the Picture Coding Symposium 2015 (Australia), the Best paper award of the International Workshop on Advanced Image Technology 2018 (Thailand), and the Ph.D. award of the Fraunhofer Portugal Challenge 2015, and the recent 2018 Outstanding reviewer award of the Elsevier Journal of Signal Processing: Image Communication.