Hoang, Van Xiem and Byeungwoo, Jeon (2018) Joint Layer Prediction for Improving SHVC Compression Performance and Error Concealment. IEEE Transactions on Broadcasting, 2018 (1). pp. 1-18. ISSN 0018-9316 (In Press)
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Abstract
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 which 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.
Item Type: | Article |
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Subjects: | Electronics and Communications Electronics and Communications > Electronics and Computer Engineering |
Divisions: | Faculty of Electronics and Telecommunications (FET) |
Depositing User: | Dr. Xiem HoangVan |
Date Deposited: | 20 Nov 2018 08:58 |
Last Modified: | 21 Nov 2018 09:07 |
URI: | http://eprints.uet.vnu.edu.vn/eprints/id/eprint/3088 |
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