Abstract
The 3D extension of High Efficiency Video Coding (3D-HEVC) introduce Depth Modeling Mode (DMM) and 35 conventional intra modes to enhance the quality of coding, while bringing unacceptable computational complexity during the process of rough mode decision (RMD) and most probable mode (MPM). In this paper, we proposed a fast mode decision algorithm for texture map and depth map coding based on gradient information. Firstly, analyzing the characteristics of predict units (PU) in different intra mode applications that obtain the lowest RD-cost,then extracting the gradient information of PU to classify the PU into three types of gradient blocks and selecting appropriate candidate modes for the PU,thereby avoiding search each mode in coding process and skip the process of RMD and MPM early. Experimental results show that the proposed algorithm can achieve average 30.6% time saving with negligible reduction of coding performance.
Highlights
3D video has received wide spread attention in recent years due to its more realistic and stereoscopic effects.3D video contains multiple viewpoints, and its data volume is much larger than 2D video, which greatly limits the application of 3D video.the Joint Collaborative Team started the research on the 3D video extension based on the High Efficiency Video Coding (HEVC) standard, namely 3D extension to High Efficiency Video Coding (3D-HEVC) [1]
3D-HEVC introduces a large number of new technologies for depth maps and 3D video features, such as Depth Image Based Rendering (DIBR), Disparity
PROPOSED FAST MODE DECISION BASED ON GRADIENT INFORMATION The introduction of intra modes in 3D-HEVC gives us a new perspective for the characteristics of various modes and novel techniques applying in the process of mode decision
Summary
The introduction of intra modes in 3D-HEVC gives us a new perspective for the characteristics of various modes and novel techniques applying in the process of mode decision. A detailed illustration of proposed intra mode decision algorithm in 3D-HEVC is presented
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