Improved joint algorithms for reliable wireless transmission of 3D color-plus-depth multi-view video

Abstract

Error control techniques like Error Resilience (ER) and Error Concealment (EC) are preferred techniques to ameliorate the lost Macro-Blocks (MBs) in the 3D Video (3DV) communication systems. In this paper, we present different enhanced ER-EC algorithms for intra-frame images for 3DV and Depth (3DV + D) communication through wireless networks. At the encoder, the slice structured coding, explicit flexible macro-block ordering, and context adaptive variable length coding are utilized. At the decoder, a hybrid approach comprising spatial circular scan order interpolation algorithm and temporal partitioning motion compensation algorithm is suggested to reconstruct the Disparity Vectors (DVs) and Motion Vectors (MVs) of the erroneous color images. For the corrupted depth images, a depth-assisted EC algorithm is proposed. Then, the optimum concealment MVs and DVs are chosen by employing the weighted overlapping block motion and disparity compensation algorithm. Furthermore, the Bayesian Kalman Filter (BKF) is utilized as an amelioration tool due to its efficiency to smooth the remnant inherent corruptions in the formerly optimally chosen color and depth DVs and MVs to obtain a good video quality. Simulation results on several 3DV streams show that the suggested algorithms have extremely adequate subjective and objective video quality performance compared to the traditional methods, particularly at high Packet Loss Rates (PLRs).