Abstract
An image quality model for smart mobile devices was proposed based on visual assessments of several image quality attributes. A series of psychophysical experiments were carried out on two kinds of smart mobile devices, i.e., smart phones and tablet computers, in which naturalness, colorfulness, brightness, contrast, sharpness, clearness, and overall image quality were visually evaluated under three lighting environments via categorical judgment method for various application types of test images. On the basis of Pearson correlation coefficients and factor analysis, the overall image quality could first be predicted by its two constituent attributes with multiple linear regression functions for different types of images, respectively, and then the mathematical expressions were built to link the constituent image quality attributes with the physical parameters of smart mobile devices and image appearance factors. The procedure and algorithms were applicable to various smart mobile devices, different lighting conditions, and multiple types of images, and performance was verified by the visual data.
© 2014 Optical Society of America
Full Article | PDF ArticleMore Like This
Youn Jin Kim, M. Ronnier Luo, Wonhee Choe, Hong Suk Kim, Seung Ok Park, Yeseul Baek, Peter Rhodes, Seongdeok Lee, and Chang Yeong Kim
J. Opt. Soc. Am. A 25(9) 2215-2222 (2008)
Muhammad Usman Khan, Ming Ronnier Luo, and Dalin Tian
J. Opt. Soc. Am. A 39(6) B65-B77 (2022)
Imran Mehmood, Xiaoxuan Liu, Muhammad Usman Khan, and Ming Ronnier Luo
J. Opt. Soc. Am. A 39(6) B11-B20 (2022)