A STATISTICAL COMPARISON OF NO-REFERENCE IMAGES QUALITY ASSESSMENT ALGORITHMS

被引：0
|
作者：
Nouri, Anass [1 ,3 ]
Charrier, Christophe
Saadane, Abdelhakim [2 ]
Fernandez-Maloigne, Christine [1 ,3 ]
机构：
[1] Univ Poitiers, XLIM SIC, UMR CNRS 7252, Futuroscope, France
[2] Univ Nantes, XLIM SIC, MR CNRS 7252, Futuroscope, France
[3] Univ Poitiers, XLIM SIC, MR CNRS 7252, Futuroscope, France
来源：
2013 COLOUR AND VISUAL COMPUTING SYMPOSIUM (CVCS) | 2013年
关键词：
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
No reference image quality metrics are of fundamental interest as they can be embedded in practical applications. This research domain is subject of intensive activities and numerous objective models have been proposed in literature. The main goal of this paper is to perform a comparative study of seven well known no-reference image quality algorithms. To test the performance of these algorithms, three public databases are used. The Spearman rank ordered correlation coefficient is utilized to measure and compare the performance. In addition, an hypothesis test is conducted to evaluate the statistical significance of performance of each tested algorithm.
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页数：5
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