Estimating print quality attributes by image quality metrics

Image quality assessment is a difficult and complex task due to its subjectivity and dimensionality. Attempts have been made to make image quality assessment more objective, such as the introduction of image quality metrics. However, it has been proven difficult to create an image quality metric correlated with perceived overall image quality. Because of this, and to reduce the dimensionality, quality attributes have been proposed to help linking subjective and objective image quality. Recently, Pedersen et al. (CIC, 2009) proposed a set of meaningful quality attributes for the evaluation of color prints with the intention of being used with image quality metrics. In this paper we evaluate image quality metrics for the quality attributes, and propose a set of suitable image quality metrics for each attribute. The experimental results indicate that the Structural SIMilarity index (SSIM) by Wang et al. (2004) is the most suitable metric for measuring the sharpness quality attribute. For the other quality attributes the results are not as conclusive.