Study of no-reference image quality assessment algorithms on printed images
Tuomas Eerola, Lasse Lensu, Heikki A. Kalviainen, Alan Conrad Bovik · Journal of Electronic Imaging · 2014
Measuring the visual quality of printed media is important since printed products have an important role in everyday life. Finding ways to automatically predict the image quality has been an active research topic in digital image processing, but adapting those methods to measure the visual quality of printed media has not been studied often or in depth and is not straightforward. Here, we analyze the efficacy of no-reference image quality assessment (IQA) algorithms originally developed for digital IQA with regards to predicting the perceived quality of printed natural images. We perform a comprehensive statistical comparison of the methods. The best methods are shown to accurately predict subjective opinions of the quality of printed photographs using data from a psychometric study.