No reference quality assessment for screen content images with both local and global feature representation

• Main Authors: Fang, Yuming, Yan, Jiebin, Li, Leida, Wu, Jinjian, Lin, Weisi
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2020
• Subjects: Engineering::Computer science and engineering; Screen Content Image; Visual Quality Assessment
• Online Access: https://hdl.handle.net/10356/142325
• Institution: Nanyang Technological University

In this paper, we propose a novel no reference quality assessment method by incorporating statistical luminance and texture features (NRLT) for screen content images (SCIs) with both local and global feature representation. The proposed method is designed inspired by the perceptual property of the h...