A two-stage H.264/AVC encoder for video streaming with fast reference picture selection
Proceedings of the 4th ACM workshop on Wireless multimedia networking and performance modeling
Error resilient video coding via weighted distortion
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
IEEE Transactions on Multimedia
IEEE Transactions on Multimedia
Prediction of transmission distortion for wireless video communication: Algorithm and application
Journal of Visual Communication and Image Representation
A joint encoder-decoder error control framework for stereoscopic video coding
Journal of Visual Communication and Image Representation
Evaluation of temporal variation of video quality in packet loss networks
Image Communication
Reference frame modification techniques for temporal and spatial scalability
Image Communication
SSIM-Based end-to-end distortion modeling for H.264 video coding
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
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For a typical video distribution system, the video contents are first compressed and then stored in the local storage or transmitted to the end users through networks. While the compressed videos are transmitted through error-prone networks, error robustness becomes an important issue. In the past years, a number of rate-distortion (R-D) optimized coding mode selection schemes have been proposed for error-resilient video coding, including a recursive optimal per-pixel estimate (ROPE) method. However, the ROPE-related approaches assume integer-pixel motion-compensated prediction rather than subpixel prediction, whose extension to H.264 is not straightforward. Alternatively, an error-robust R-D optimization (ER-RDO) method has been included in H.264 test model, in which the estimate of pixel distortion is derived by simulating decoding process multiple times in the encoder. Obviously, the computing complexity is very high. To address this problem, we propose a new end-to-end distortion model for R-D optimized coding mode selection, in which the overall distortion is taken as the sum of several separable distortion items. Thus, it can suppress the approximation errors caused by pixel averaging operations such as subpixel prediction. Based on the proposed end-to-end distortion model, a new Lagrange multiplier is derived for R-D optimized coding mode selection in packet-loss environment by taking into account of the network conditions. The rate control and complexity issues are also discussed in this paper