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Combined Full-Reference Image Quality Metrics for Objective Assessment of Multiply Distorted Images

Krzysztof Okarma, Piotr Lech, Vladimir Lukin

2021Electronics19 citationsDOIOpen Access PDF

Abstract

In the recent years, many objective image quality assessment methods have been proposed by different researchers, leading to a significant increase in their correlation with subjective quality evaluations. Although many recently proposed image quality assessment methods, particularly full-reference metrics, are in some cases highly correlated with the perception of individual distortions, there is still a need for their verification and adjustment for the case when images are affected by multiple distortions. Since one of the possible approaches is the application of combined metrics, their analysis and optimization are discussed in this paper. Two approaches to metrics’ combination have been analyzed that are based on the weighted product and the proposed weighted sum with additional exponential weights. The validation of the proposed approach, carried out using four currently available image datasets, containing multiply distorted images together with the gathered subjective quality scores, indicates a meaningful increase of correlations of the optimized combined metrics with subjective opinions for all datasets.

Topics & Concepts

Computer scienceImage qualityQuality (philosophy)CorrelationArtificial intelligenceImage (mathematics)Data miningPattern recognition (psychology)Machine learningMathematicsPhilosophyEpistemologyGeometryImage and Video Quality AssessmentAdvanced Image Fusion TechniquesImage Enhancement Techniques
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