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基于合成视频感知质量的高效3D深度编码

High-Efficiency 3D Depth Coding Based on Perceptual Quality of Synthesized Video.

出版信息

IEEE Trans Image Process. 2016 Dec;25(12):5877-5891. doi: 10.1109/TIP.2016.2615290. Epub 2016 Oct 5.

DOI:10.1109/TIP.2016.2615290
PMID:28113503
Abstract

In 3D video systems, imperfect depth images often induce annoying temporal noise, e.g., flickering, to the synthesized video. However, the quality of synthesized view is usually measured with peak signal-to-noise ratio or mean squared error, which mainly focuses on pixelwise frame-by-frame distortion regardless of the obvious temporal artifacts. In this paper, a novel full reference synthesized video quality metric (SVQM) is proposed to measure the perceptual quality of the synthesized video in 3D video systems. Based on the proposed SVQM, an improved rate-distortion optimization (RDO) algorithm is developed with the target of minimizing the perceptual distortion of synthesized view at given bit rate. Then, the improved RDO algorithm is incorporated into the 3D High Efficiency Video Coding (3D-HEVC) software to improve the 3D depth video coding efficiency. Experimental results show that the proposed SVQM metric has better consistency with human perception on evaluating the synthesized view compared with the state-of-the-art image/video quality assessment algorithms. Meanwhile, this SVQM metric maintains low complexity and easy integration to the current video codec. In addition, the proposed SVQM-based depth coding scheme can achieve approximately 15.27% and 17.63% overall bit rate reduction or 0.42- and 0.46-dB gain in terms of SVQM quality score on average as compared with the latest 3D-HEVC reference model and the state-of-the-art depth coding algorithm, respectively.

摘要

在3D视频系统中,不完善的深度图像常常会给合成视频带来恼人的时间噪声,例如闪烁。然而,合成视图的质量通常用峰值信噪比或均方误差来衡量,这主要关注逐像素的逐帧失真,而忽略了明显的时间伪像。本文提出了一种新颖的全参考合成视频质量度量(SVQM),用于测量3D视频系统中合成视频的感知质量。基于所提出的SVQM,开发了一种改进的率失真优化(RDO)算法,目标是在给定比特率下最小化合成视图的感知失真。然后,将改进的RDO算法纳入3D高效视频编码(3D-HEVC)软件中,以提高3D深度视频编码效率。实验结果表明,与现有最先进的图像/视频质量评估算法相比,所提出的SVQM度量在评估合成视图时与人类感知具有更好的一致性。同时,该SVQM度量保持低复杂度且易于集成到当前视频编解码器中。此外,与最新的3D-HEVC参考模型和现有最先进的深度编码算法相比,所提出的基于SVQM的深度编码方案平均在总体比特率降低方面可分别实现约15.27%和17.63%,或者在SVQM质量得分方面实现0.42 dB和0.46 dB的增益。

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