Abstract
In this paper, a low-complexity algorithm is proposed to reduce the complexity of depth map compression in the high-efficiency video coding (HEVC)-based 3D video coding (3D-HEVC). Since the depth map and the corresponding texture video represent the same scene in a 3D video, there is a high correlation among the coding information from depth map and texture video. An experimental analysis is performed to study depth map and texture video correlation in the coding information such as the motion vector and prediction mode. Based on the correlation, we propose three efficient low-complexity approaches, including early termination mode decision, adaptive search range motion estimation (ME), and fast disparity estimation (DE). Experimental results show that the proposed algorithm can reduce about 66% computational complexity with negligible rate-distortion (RD) performance loss in comparison with the original 3D-HEVC encoder.
Highlights
Three-dimensional video standard has been recently finalized by the Joint Collaborative Team on 3D Video Coding (JCT-3V), and the high-efficiency video coding (HEVC)-based 3D video coding (3D-HEVC) is developed as an extension of HEVC [1,2,3]
This paper proposes an early termination mode decision for 3DHEVC, which takes into account the correlations between coding information from texture videos and depth maps to speed up the coding process
4 Experimental results In order to confirm the performance of the proposed low-complexity depth map compression algorithm, which is implemented on the recent 3D-HEVC Test Model (HTM ver.5.1), we show the results obtained in the test on eight sequences released by the JCT-3V Group
Summary
Three-dimensional video standard has been recently finalized by the Joint Collaborative Team on 3D Video Coding (JCT-3V), and the high-efficiency video coding (HEVC)-based 3D video coding (3D-HEVC) is developed as an extension of HEVC [1,2,3]. The proposed algorithm consists of three approaches: early termination mode decision, adaptive search range ME, and fast disparity estimation (DE) for depth map coding.
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