Extended Hybrid Image Similarity – Combined Full-Reference Image Quality Metric Linearly Correlated with Subjective Scores
Keywords:Image quality assessment, image analysis, image similarity
AbstractOne of the most relevant issues in image processing and analysis is a reliable image quality assessment. During last several years numerous metrics have been proposed by various researchers which are much better than traditionally used Mean Squared Error or similar metrics in the aspect of the accordance with human perception of various distortions. Nevertheless, the direct application of such metrics does not provide high correlation with subjective scores because of the required additional nonlinear mapping. Unfortunately, such fitting, typically applied for each image database using the logistic function, leads to different values of parameters for each dataset. As a more universal approach, some nonlinear combinations of various metrics have been proposed recently which do not require any nonlinear mapping. In the paper an extended combined similarity metric is proposed, which provides high prediction accuracy of the image quality with highly linear correlation with subjective scores. The results of extensive tests conducted using the most relevant image quality assessment databases are also presented.
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