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首页> 外文会议>Conference on Applied Mechanis, Materials and Manufacturing >New just-Noticeable-Distortion model based on the depth information and its application in Multiview Video Coding
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New just-Noticeable-Distortion model based on the depth information and its application in Multiview Video Coding

机译：基于深度信息及其在多视图视频编码中的新刚刚明显的失真模型

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摘要

To reach higher compression ratios without perceptually degrading the reconstructed signal, the properties of the human visual system (HVS) need to be better exploited. Research simulated the sensitivity of HVS with the just-noticeable-distortion (JND) model, which describes the perception redundancy quantitatively. This paper proposed a new JND model in multiview video coding (MVC) which explored the property of HVS to stereoscopic masking effect. The proposed model contained the spatial JND, temporal JND and the JND in depth. A novel asymmetric stereoscopic video coding method was proposed based on the new JND model. For each macroblock (MB), the quantization parameters (QPs) were optimized adaptively based on the new JND. Compared with the original JMVC scheme without JND, our method gets remain perceptual quality and save bits averagely 24.18%~36.24%.
机译：为了达到较高的压缩比而不感知地降低重建信号，需要更好地利用人类视觉系统（HVS）的性质。研究模拟了HV与刚性 - 失真（JND）模型的灵敏度，其定量描述了感知冗余。本文提出了一种在多视图视频编码（MVC）中的新JND模型，该模型探讨了HVS的属性来立体屏蔽效果。所提出的模型包含空间JND，时间JND和JND深度。基于新的JND模型提出了一种新的非对称立体视频编码方法。对于每个宏块（MB），基于新JND自适应地优化量化参数（QPS）。与未经JND的原始JMVC方案相比，我们的方法保持了感知质量，并节省比特，平均为24.18％〜36.24％。

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