Title: Perceptual image quality assessment based on gradient similarity and Ruderman operator

Authors: Ahmed Zeggari; Zianou Ahmed Seghir; Mounir Hemam

Addresses: Computer Sciences Department, University of Tebessa, Constantine Road, 12000 Tebessa, Algeria ' ICOSI Laboratory, Faculty ST, University Khenchela, BP 1252 El Houria, 40004 Khenchela, Algeria ' ICOSI Laboratory, Faculty ST, University Khenchela, BP 1252 El Houria, 40004 Khenchela, Algeria

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.

Keywords: Ruderman operator; gradient similarity; image quality assessment; IQA; objective methods; human visual system.

DOI: 10.1504/IJCVR.2021.113402

International Journal of Computational Vision and Robotics, 2021 Vol.11 No.2, pp.151 - 174

Accepted: 21 Sep 2019
Published online: 03 Mar 2021 *

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