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No-Reference Image Quality Assessment in Spatial Domain

机译:空间域中的无参考图像质量评估

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With the development of computer vision, there has been an increasing need to develop objective quality measurement techniques that can predict image quality automatically. In this paper, we present a complex Noreference image quality assessment (NR IQA) algorithm, which mainly consists of two steps. The first step uses Gabor filters to obtain the feature images with different frequencies and orientations, so as to extract the energy and entropy features of each sub-image. The second step uses the Linear least squares to obtain the parameters for IQA. We conduct experiments in LIVE IQA Database to verify our method. The experimental results show that the proposed method is much more competitive than other state of the art Full-reference (FR) or NR algorithms.
机译:随着计算机愿景的发展,越来越需要开发客观质量测量技术,可以自动预测图像质量。在本文中,我们提出了一种复杂的阅览室图像质量评估(NR IQA)算法,主要由两个步骤组成。第一步使用Gabor滤波器来获得具有不同频率和方向的特征图像,从而提取每个子图像的能量和熵特征。第二步使用线性最小二乘来获得IQA的参数。我们在Live IQA数据库中进行实验以验证我们的方法。实验结果表明,所提出的方法比其他最先进的完整参考(FR)或NR算法更具竞争力。

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