No abstract

No abstract

No abstract

Prospective 3D video transmission systems that would use compression of both multiview video and depth maps was dealt with in this paper. To get the optimal synthesized view quality with the transmission bit rate being constant, it firstly analyzed the overall behavior of combined coding and view synthesis, color and depth data with different coding qualities were combined for intermediate view synthesis. Then, individual coding results for color and depth data were evaluated in order to investigate, how well the synthesized view quality was at certain compression. Finally, a new joint coding method for multi-view video plus depth (MVD) was proposed by utilizing the optimal combinations of the quantization parameters of color videos and the corresponding depth maps. Simulation results demonstrated that the proposed method decreased the bit-rate by 12.72%~24.02% in comparison with JMVC and can be used to guide sequence-level texture/depth coding for 3D video compression. The proposed method has better performance in optimizing the tradeoff between bit-rate and visual quality

As a 3D extension to the High Efficiency Video Coding (HEVC) standard, 3D-HEVC was developed to improve the coding efficiency of multiview videos. It inherits the prediction modes from HEVC, yet both Motion Estimation (ME) and Disparity Estimation (DE) are required for dependent views coding. This improves coding efficiency at the cost of huge computational costs. In this article, an early Merge mode decision approach is proposed for dependent texture views and dependent depth maps coding in 3D-HEVC based on priori and posterior probability models. First, the priori probability model is established by exploiting the hierarchical and interview correlations from those previously encoded blocks. Second, the posterior probability model is built by using the Coded Block Flag (CBF) of the current coding block. Finally, the joint priori and posterior probability model is adopted to early terminate the Merge mode decision for both dependent texture views and dependent depth maps coding. Experimental results show that the proposed approach saves 45.2% and 30.6% encoding time on average for dependent texture views and dependent depth maps coding while maintaining negligible loss of coding efficiency, respectively.