Visual Attention in Quality Assessment

Document type: Journal Articles
Article type: Original article
Peer reviewed: Yes
Author(s): Ulrich Engelke, Hagen Kaprykowsky, Hans-Jürgen Zepernick, Patrik Ndjiki-Nya
Title: Visual Attention in Quality Assessment
Journal: IEEE Signal Processing Magazine
Year: 2011
Volume: 28
Issue: 6
Pagination: 50-59
ISSN: 1053-5888
Publisher: IEEE
URI/DOI: 10.1109/MSP.2011.942473
ISI number: 000296466100007
Organization: Blekinge Institute of Technology
Department: School of Computing (Sektionen för datavetenskap och kommunikation)
School of Computing S-371 79 Karlskrona
+46 455 38 50 00
Authors e-mail:,,,
Language: English
Abstract: Perceptual quality metrics are widely deployed in image and video processing systems. These metrics aim to emulate the integral mechanisms of the human visual system (HVS) to correlate well with visual perception of quality. One integral property of the HVS is, however, often neglected: visual attention (VA) [1]. The essential mechanisms associated with VA consist mainly of higher cognitive processing, deployed to reduce the complexity of scene analysis. For this purpose, a subset of the visual information is selected by shifting the focus of attention across the visual scene to the most relevant objects. By neglecting VA, perceptual quality models inherently assume that all objects draw the attention of the viewer to the same degree.
Subject: Signal processing\Image and Video Processing
Keywords: Computational modeling , Image processing , Measurement , Quality assessment , Visualization