Color Gaussian Jet Features For No-Reference Quality Assessment of Multiply-Distorted Images

被引:13
|
作者
Hadizadeh, Hadi [1 ]
Bajic, Ivan V. [2 ]
机构
[1] Quchan Univ Adv Technol, Quchan, Iran
[2] Simon Fraser Univ, Burnaby, BC V5A 1S6, Canada
关键词
Gaussian jet; image quality assessment (IQA); local binary pattern (LBP); GRADIENT MAGNITUDE; NATURAL IMAGES; STATISTICS; DOMAIN; SIMILARITY; SALIENCY; INDEX;
D O I
10.1109/LSP.2016.2617743
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this letter we present a novel no-reference image quality assessment (NR-IQA) method for the visual quality prediction of multiply-distorted color images. In the proposed method, to describe the image structure, a number of feature maps are first calculated based on the color Gaussian jet of the image. The popular local binary pattern operator is then applied on the computed feature maps to measure any potential structural degradations caused by multiple distortions. The performance of the proposed method was compared with 14 prominent full-reference IQA methods as well as 11 NR-IQA methods on two multidistortion IQA databases. The results indicate that the proposed method outperforms all the compared methods with a high accuracy at a moderate complexity.
引用
收藏
页码:1717 / 1721
页数:5
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