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Full-reference stereoscopic image quality assessment accounting for binocular combination and disparity information

机译:考虑到双目组合和视差信息的全参考立体图像质量评估

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One of the most challenging issues in stereoscopic image quality assessment (SIQA) is how to effectively model the binocular behavior of the human visual system (HVS). The latter has a great impact on the perceptual 3D quality. In this paper, we propose a SIQA metric accounting for binocular combination properties and disparity information. Instead of computing the quality of the left and the right views separately, the proposed metric predicts the quality of a cyclopean image so as to have a good consistency with 3D human perception. The cyclopean image is synthesized based on the local entropy and the visual saliency of each view with the aim to simulate the phenomena of binocular fusion/rivalry. A 2D IQA metric is employed to assess the quality of both the cyclopean image and the disparity map. The obtained scores are used to derive the 3D quality score thanks to a pooling stage. Experimental results on three public 3D IQA databases show that the proposed method outperforms many other state-of-the-art SIQA methods, and achieves high prediction accuracy on these databases.
机译:立体图像质量评估(SIQA)中最具挑战性的问题之一是如何有效地模拟人类视觉系统(HVS)的双目行为。后者对3D感知质量有很大影响。在本文中,我们提出了一种SIQA度量标准,用于解释双目组合属性和视差信息。代替单独计算左视图和右视图的质量,所提出的度量标准预测了独眼巨人图像的质量,从而与3D人类感知具有良好的一致性。基于局部熵和每个视图的视觉显着度合成独眼巨人的图像,目的是模拟双眼融合/竞争的现象。使用2D IQA度量来评估独眼巨人图像和视差图的质量。由于汇集阶段,所获得的分数可用于得出3D质量分数。在三个公共3D IQA数据库上的实验结果表明,该方法优于许多其他最新的SIQA方法,并在这些数据库上实现了较高的预测精度。

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