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The effect of depth map up-sampling on the overall quality of stereopairs

机译:深度图上采样对立体声对整体质量的影响

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摘要

The quality of depth maps affects the quality of generated 3D content. Practically, the depth maps often have lower resolution than that of color images, thus, Depth map Up-sampling (DU) is needed in various 3D applications. DU can yield specific artifacts which can degrade the quality of depth maps as well as constructed stereoscopic (color plus depth map) images. This paper investigates the effect of DU on 3D perception. The depth maps were up-sampled using seven approaches and the quality of stereoscopic images obtained from up-sampled depth maps was estimated through subjective and objective tests. The objective quality prediction was performed using a depth map quality assessment framework. The method is able to predict the quality of stereoscopic images through evaluation of their corresponding up-sampled depth maps using 2D Image Quality Metrics (IQMs). In order to improve the quality estimation, the framework selects the 2D IQMs with highest correlation to subjective test. Furthermore, motivated by previous researches on multiple metrics combination, a new metric fusion method is proposed. Experimental results show that the combined metric delivers higher performance than single metrics in 3D quality prediction.
机译:深度图的质量会影响生成的3D内容的质量。实际上,深度图通常比彩色图像具有更低的分辨率,因此,在各种3D应用程序中都需要深度图上采样(DU)。 DU会产生特定的伪影,这些伪影会降低深度图以及构造的立体(颜色加深度图)图像的质量。本文研究了DU对3D感知的影响。使用七种方法对深度图进行了上采样,并通过主观和客观测试评估了从上采样深度图获得的立体图像的质量。使用深度图质量评估框架执行客观质量预测。该方法能够通过使用2D图像质量度量(IQM)评估相应的上采样深度图来预测立体图像的质量。为了提高质量估计,框架选择与主观测试相关性最高的二维IQM。此外,在先前关于多指标组合的研究的启发下,提出了一种新的指标融合方法。实验结果表明,在3D质量预测中,组合指标比单个指标具有更高的性能。

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