Reduced-reference quality assessment of image super-resolution by energy change and texture variation

• Main Authors: Fang, Yuming, Liu, Jiaying, Zhang, Yabin, Lin, Weisi, Guo, Zongming
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Computer science and engineering; Image Quality Assessment; Image Super-resolution
• Online Access: https://hdl.handle.net/10356/147379
• Institution: Nanyang Technological University

In this paper, we propose a novel reduced-reference quality assessment metric for image super-resolution (RRIQA-SR) based on the low-resolution (LR) image information. With the pixel correspondence, we predict the perceptual similarity between image patches of LR and SR images by two components: the...