Screen Content Image Quality Assessment Using Multi-Scale Difference of Gaussian

Screen Content Image Quality Assessment Using Multi-Scale Difference of Gaussian
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使用多尺度高斯差分的屏幕内容图像质量评估

DOI:
10.1109/tcsvt.2018.2854176
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发表时间:
2018-07
影响因子:
8.4
通讯作者:
Ma Kai Kuang
Ma Kai Kuang
中科院分区:
工程技术1区
文献类型:
--
作者:
Fu Ying;Zeng Huanqiang;Ma Lin;Ni Zhangkai;Zhu Jianqing;Ma Kai Kuang

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本文提出了一种基于多尺度高斯差分(MDOG)的屏幕内容图像质量评估模型。基于人类视觉系统对边缘敏感,而在不同尺度下可以更好地挖掘图像细节的特点,该模型利用MDOG分别在两种不同尺度下有效表征参考和扭曲SCIs的边缘信息。然后,根据小比例尺边缘图测量边缘相似度。最后,将基于大比例尺边缘图计算的边缘强度作为加权因子,生成最终的SCI质量分数。实验结果表明,本文提出的SCI质量IQA模型与人类对SCI质量的感知具有较高的一致性,并且优于现有的SCI质量模型。
In this paper, a novel image quality assessment (IQA) model for the screen content images (SCIs) is proposed by using multi-scale difference of Gaussian (MDOG). Motivated by the observation that the human visual system (HVS) is sensitive to the edges while the image details can be better explored in different scales, the proposed model exploits MDOG to effectively characterize the edge information of the reference and distorted SCIs at two different scales, respectively. Then, the degree of edge similarity is measured in terms of the smaller-scale edge map. Finally, the edge strength computed based on the larger-scale edge map is used as the weighting factor to generate the final SCI quality score. Experimental results have shown that the proposed IQA model for the SCIs produces high consistency with human perception of the SCI quality and outperforms the state-of-the-art quality models.
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