Perceptual image quality assessment based on gradient similarity and Ruderman operator. (10th December 2020)

• Record Type: Journal Article
• Authors: Zeggari, Ahmed; Seghir, Zianou Ahmed; Hemam, Mounir
• Is Part Of: International journal of computational vision and robotics. Volume 11:Number 2(2021)
• Page Start: 151
• Page End: 174
• Publication Date: 2020-12-10
• Subjects: Ruderman operator -- gradient similarity -- image quality assessment -- IQA -- objective methods -- human visual system; Computer vision -- Periodicals; Robotics -- Periodicals; Artificial intelligence -- Periodicals; 006.3705
• Languages: English
• ISSNs: 1752-9131

Abstract

In this work, a new metric for image quality assessment is suggested, which provides more suppleness than previous measures in using Ruderman operator, visual region of interest and gradient similarity. Firstly, the luminance distortion between the reference and test images is determined. Secondly, the gradient similarity is computed by using canny filter and proposed gradient mask. Thirdly, the test and reference images are transformed using Ruderman operator. Fourthly, the visual region of interest is calculated by employing entropy operator. Lastly, the dissimilarity between the reference and test images is obtained, by combining all previous metrics: luminance distortion measure, gradient similarity measures, Ruderman measure and visual region of interest measure. Experimental comparison demonstrates the effectiveness of the proposed method.