Abstract
Recently, various objective image quality assessment (IQA) metrics have been proposed for measuring the quality of a captured image. Moreover, IQA databases have been made available to enable researchers develop and test IQA metrics. For instance, the TID2013 database was used in the experiments conducted in this study. It contains many test images obtained from 25 reference images, each having 24 types of distortion and five levels of noise for each distortion. However, estimating a subjective evaluation score for many types of noise is a difficult task. Therefore, this study proposes an objective IQA framework for evaluating noise clusters using image features. Experimental results confirmed the effectiveness of the proposed framework.
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