Fast mode decision algorithm for 3D-HEVC encoding optimization based on depth information
The advanced 3D extension of the High Efficiency Video Coding standard (3D-HEVC) encodes 3D videos in the multi-view video plus depth format (MVD) and introduces new prediction modes to improve the coding performance of dependent views and depth data. Similar to HEVC, the mode decision process in 3D-HEVC is performed using a large number of prediction modes to find the one mode with the least rate distortion (RD) cost using Lagrange multiplier. These techniques achieve the highest possible coding efficiency, but also bring high computational complexity, which may limit the use of 3D-HEVC in practical applications. In this paper, we propose a fast mode decision algorithm based on the depth information to reduce 3D-HEVC computational complexity. Since the video texture and depth map are highly content-dependent, it is not efficient to use all the prediction modes in 3D-HEVC mode decision procedure. There exist high correlations of the coding information when two CUs have the similar depth values. Based on the correlations, we propose two efficient mode decision techniques, 1) an early coding level determination is developed based on the spatially neighboring CUs depth values; 2) an adaptive mode size decision is introduced based on the correlations between the motion characteristics and the depth values. Experimental results show that the proposed algorithm can save 74% computational complexity on average with only 1.47% increase on bit rate or 0.06 dB loss on peak signal-to-noise ratio (PSNR) compared with the original 3D-HEVC encoder.
mode decision 3d-hevc depth map correlation