Subjective and Objective Quality Assessment of Compressed Screen Content Images
Subjective and Objective Quality Assessment of Compressed Screen Content Images
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DOI：
10.1109/jetcas.2016.2598756
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发表时间：
2016-12-01
影响因子：
4.6
通讯作者：
Gao, Wen
中科院分区：
文献类型：
--
作者：
Wang, Shiqi;Gu, Ke;Gao, Wen
客观地评估屏幕内容图像（SCI）的质量是一个具有挑战性的问题，因为SCI可能并不总是具有与自然场景相同的属性。在这里，我们进行全面的研究压缩SCI的主观和客观质量评估。首先，我们建立了一个数据库，其中包含了高效率视频编码标准及其在屏幕内容压缩上的扩展所产生的失真SCI。随后，进行主观实验，以评估这些SCI与压缩伪影的感知质量。为了自动预测的主观质量，减少参考质量评估模型进一步学习的一组小波域特征的广义光谱行为，波动的能量，和相对大规模的训练样本的信息内容。我们的实验结果表明，学习模型是能够实现更好的预测SCI质量与一些提取有意义的功能。
Objectively accessing the quality of screen content images (SCIs) is a challenging problem, as SCIs may not always have identical properties as natural scenes. Here we conduct comprehensive studies on the subjective and objective quality assessment of the compressed SCIs. Firstly, we build a database that contains the distorted SCIs generated by the high efficiency video coding standard as well as its extension on screen content compression. Subsequently, subjective experiments are conducted to evaluate the perceived quality of these SCIs with compression artifacts. To automatically predict the subjective quality, a reduced-reference quality assessment model is further learnt by a set of wavelet domain features concerning the generalized spectral behavior, the fluctuations of the energy, and the information content with relatively large scale training samples. Our experimental results show that the learnt model is able to achieve better prediction on the SCI quality with a few extracted meaningful features.