Fast Algorithms for Inter-view Prediction of Multiview Video Coding

Abstract

The compression efficiency and complexity should be simultaneously taken into consideration in Multiview Video Coding (MVC). In order to reduce the complexity while maintaining the efficiency of MVC, we proposed in this paper two algorithms called Adaptive Search Region Adjustment (ASRA) and Adaptive Selection of Inter-view References (ASIR). In ASRA, we simplified the exiting method to obtain the global disparity vector (GDV), using which the correlations between the disparity vector (DV) and predicted vector were exploited. The statistical property of the absolute difference value of $DV$ and GDV was analyzed and the results were applied to adjust the search range dynamically. In ASIR, we first used the prediction information of the lower temporal layer in the hierarchical B picture prediction structure to reduce the number of inter-view reference pictures, and then applied the results of reference selection after inter_16×16 prediction mode decision to revise our method. The experimental results demonstrate that the algorithms suggested in this paper can reduce the computation up to 25% with little decrease of compression efficiency.