AUTO-REGRESSIVE MODEL BASED ERROR CONCEALMENT SCHEME FOR STEREOSCOPIC VIDEO CODING

Stereoscopic and 3-D Coding

Přednášející: Xinguang Xiang, Autoři: Xinguang Xiang, Debin Zhao, Harbin Institute of Technology, China; Siwei Ma, Wen Gao, Peking University, China

Stereoscopic video is an important manner for 3-D video applications, and robust stereoscopic video transmission has posed a technical challenge for stereoscopic video coding. In this paper, an auto-regressive (AR) model based error concealment scheme is proposed for stereoscopic video coding to address the challenging problem. The proposed error concealment scheme includes a temporal AR model for independent view, and a temporal-interview AR model for inter-view predicted view. First, appropriate motions and disparities for lost blocks are derived. Then, the proposed AR model coefficients are computed according to the spatial neighboring pixels and their temporal-correlated and interview-correlated pixels indicated by the selected prediction directions. Finally, applying the AR model, each pixel of the lost block is interpolated as a weighted summation of pixels in the reference frame along the selected prediction directions. Simulation results show that the performance of the proposed scheme is superior to conventional temporal error concealment methods for stereoscopic video coding.

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