Effective multi-stage error control algorithms for robust 3D video transmission over wireless networks
- 62 Downloads
The Three-Dimensional Video (3DV) contains diverse video streams taken by different cameras around an object. Thence, it is an imperative assignment to fulfill efficient compression to match the future resource limitations, whilst preserving a decisive reception 3DV quality. The efficient 3DV communication over wireless networks has become a recent considerable hot issue due to the restricted resources and the presence of severe channel errors. The high-rate 3DV encoding and transmission over mobile or Internet are vulnerable to packet losses due to the existence of heavy channel losses and limited bandwidth. Therefore, this paper presents efficient multi-stage error control algorithms for reliable 3DV transmission over error-prone wireless channels. At the encoder, the error resilience schemes of context adaptive variable length coding, slice structured coding, and explicit flexible macro-block ordering are utilized. At the decoder, a joint approach of a directional interpolation error concealment algorithm and a directional textural motion coherence algorithm is proposed to conceal the corrupted color frames. For the concealment of the lost depth frames, an encoder independent decoder dependent depth-assisted error concealment algorithm is suggested. Moreover, the weighted overlapping block motion and disparity compensation algorithm is exploited to choose the candidate concealment Motion Vectors (MVs) and Disparity Vectors (DVs). Furthermore, an improved recursive Bayesian filtering algorithm is utilized as a refinement stage to smooth the remaining errors in the previously selected candidate MVs and DVs for achieving better 3DV quality. Simulation results on several 3DV sequences show that the proposed algorithms achieve adequate objective and subjective 3DV quality performance at severe packet loss rates compared to the state-of-the-art algorithms.
Keywords3D video Error control Motion and disparity compensation Bayesian Kalman Filter Quality assessment Wireless channel
- 2.Xiang, W., Gao, P., & Peng, Q. (2015). Robust multiview three-dimensional video communications based on distributed video coding. IEEE Systems Journal, 99, 1–11.Google Scholar
- 6.Shokrollahi, M. (2014). Error-correcting multi-stage code generator and decoder for communication systems having single transmitters or multiple transmitters. U.S. Patent, 8, 887, 020.Google Scholar
- 9.El-Shafai, W., Hrušovský, B., El-Khamy, M., El-Sharkawy, M. (2011). Joint space-time-view error concealment algorithms for 3D multi-view video. In 18th IEEE international conference on image processing (ICIP) (pp. 2201–2204).Google Scholar
- 10.El-Shafai, W. (2013) Optimized adaptive space-time-view multi-dimentional error concealment for 3D multi-view video transmission. In IEEE Saudi international electronics, communications and photonics conference (SIECPC) (pp. 1–6).Google Scholar
- 13.Yang, D., Liu, T., Liu, S. M., Chen, F. C. (2016). An adaptive spatial-temporal error concealment scheme based on H.264/AVC. In A. Hussain (Ed.), Electronics, communications and networks V. Lecture notes in electrical engineering (Vol. 382). Singapore: Springer.Google Scholar
- 16.Ibrahim, A., Sadka, A. (2014). Error resilience and concealment for multiview video coding. In Proceedings of the IEEE international symposium on broadband multimedia systems and broadcasting (pp. 1–5).Google Scholar
- 18.Memon, M., Khan, A., Li, J., Shaikh, R., & Memon, I., Deep, S. (2014). Content based image retrieval based on geo-location driven image tagging on the social web. In 11th IEEE international computer conference on wavelet active media technology and information processing (ICCWAMTIP) (pp. 280–283).Google Scholar
- 19.Vetrivel, S., & Athisha, G. (2014). Video streaming: Single and compound report transcoding method. Asian Journal of Information Technology, 13, 300–307.Google Scholar
- 20.Memon, M., Shaikh, R., Li, J., Khan, A., Memon, I., & Deep, S. (2014). Unsupervised feature approach for content based image retrieval using principal component analysis. In 11th IEEE international computer conference on wavelet active media technology and information processing (ICCWAMTIP) (pp. 271–275).Google Scholar
- 21.Memon, M., Li, J., Memon, I., Shaikh, R., & Mangi, F. (2015). Efficient object identification and multiple regions of interest using CBIR based on relative locations and matching regions. In 12th IEEE international computer conference on Wavelet active media technology and information processing (ICCWAMTIP) (pp. 247–250).Google Scholar
- 22.Salim, O., Xiang, W., & Leis, J. (2013). An efficient unequal error protection scheme for 3-D video transmission. In Proceedings of the IEEE wireless communications and networking conference (WCNC) (pp. 4077–4082).Google Scholar
- 30.Wang, H., & Wang, X. (2016). Important macroblock distinction model for multi-view plus depth video transmission over error-prone network. Multimedia Tools and Applications, 1–23.Google Scholar
- 31.H.264/AVC codec; September 2016. http://iphome.hhi.de/suehring/tml/.
- 32.Xiang, X., Zhao, D., Wang, Q., Ji, X., & Gao, W. (2007). A novel error concealment method for stereoscopic video coding. In Proceedings of the IEEE international conference on image processing (pp. 101–104).Google Scholar
- 33.Gao, Z., & Lie, W. (2004). Video error concealment by using Kalman-filtering technique. In Proceedings of the IEEE international symposium on circuits and systems (pp. 69–72).Google Scholar
- 37.ISO/IEC JTC1. (2006). Common test conditions for multiview video coding (JVT-U207) (pp 1–9).Google Scholar
- 38.WD 4 reference software for multiview video coding (mvc); August 2016. http://wftp3.itu.int/av-arch/jvt-site/2009_01_Geneva/JVT-AD207.zip.