Error Resilient Video Coding Using Redundant Pictures
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resilience video coding parameters and mechanisms selection with End-to-End rate-distortion analysis at frame levelAuthorsAuthors and http://link.springer.com/article/10.1007/s11042-014-2409-0 affiliationsWeiwei XuEmail authorYaowu ChenArticleFirst Online: 28 December 2014Received: 12 May 2014Revised: 19 November 2014Accepted: 01 December 2014DOI: 10.1007/s11042-014-2409-0Cite this article as: Xu, W. & Chen, Y. Multimed Tools Appl (2016) 75: 2347. doi:10.1007/s11042-014-2409-0 99 Views AbstractTo improve the quality of video transmission, a fast error resilience coding method based error resilient on frame level rate-distortion analysis is proposed. To constrain the accumulated error propagation distortion and error concealment distortion simultaneously, reference frame selection and intra/inter mode decision are jointly used with redundant pictures. An adaptive multiple redundant picture (AMRP) coding mechanism is used for redundant picture coding with error resilient video the adaptively estimated number of redundant pictures and encoding parameter for each specific redundant picture. The encoding parameters of different frames are adjusted based on the distortion propagation. We propose a statistical model for efficiently estimating the distortion and rate of the primary and the redundant picture. The total distortion and rate of the primary and the redundant picture are then formulated as a function of the quantization parameter, the temporal prediction distance, and the error resilient configuration. Lastly, the end-to-end rate-distortion optimized selection of the encoding parameters and coding structure is efficiently performed considering error propagation. Experimental results demonstrate that the proposed algorithm exhibits significant performance gains over the state-of-the-art error-resilient encoding methods.KeywordsVideo codingError resilientEnd-to-End distortionRate-distortion optimizationReference frame selectionRedundant pictureReferences1.Chen ZF, Wu DP (2012) Prediction of transmission distortion for wireless video communication: analysis. IEEE Trans Image Process 21(3):1123–1137CrossRefMathSciNetGoogle Scholar2.F
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