Statistical comparison of no-reference images quality assessment algorithms
Anass Nouri, Christophe Charrier, Abdelhakim Saadane, Christine Fernández-Maloigne · 2013
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.