Non-distortion-specific no-reference image quality assessment using Statistical Features

Non-distortion-specific no-reference image quality assessment is one of the challenges in the field of digital image processing. This is because there are no reference images, the type of failure, scores, and scoring of a human observer while this field is used in various applications. The purpose of this paper is to use the properties and characteristics of the images and model them with the q-Gaussian distribution for evaluation of image quality. The q-Gaussian distribution is one of the options that creates the boundaries of flexibility decision making with different Gaussian forms that have more generalizability in abnormalities than other distributions, and to better model the statistical properties of the image. Our experimental results show that the performance of the proposed technique is more than other distribution.