SECOND ORDER NATURAL SCENE STATISTICS MODEL OF BLIND IMAGE QUALITY ASSESSMENT

被引：0
|
作者：
Sinno, Zeina [1 ]
Caramanis, Constantine [1 ]
Bovik, Alan [1 ]
机构：
[1] Univ Texas Austin, Dept Elect & Comp Engn, Austin, TX 78712 USA
来源：
2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2018年
关键词：
Second Order Natural Scene Statistics; Blind Image Quality Assessment; Multimedia;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
The univariate statistics of bandpass-filtered images provide powerful features that drive many successful image quality assessment (IQA) algorithms. Bivariate Natural Scene Statistics (NSS), which model the joint statistics of multiple bandpass image samples also provide potentially powerful features to assess the perceptual quality of images, by capturing both image and distortion correlations. Here, we make the first attempt to use bivariate NSS features to build a model of no-reference image quality prediction. We show that our bivariate model outperforms existing state of the art image quality predictors.
引用
收藏
页码：1238 / 1242
页数：5
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