Perceptual representations of structural information in images: application to quality assessment of synthesized view in FTV scenario
This addresses the challenge of quality assessment for immersive multimedia content like FTV, which is incremental as it builds on hierarchical visual representations to improve existing metrics.
The paper tackles the problem of assessing quality in Free-viewpoint TV (FTV) synthesized views, where distortions are non-uniform and structure-related, by proposing a bio-inspired full-reference image quality metric based on hierarchical structural representations. The experimental results show that the proposed model significantly outperforms state-of-the-art metrics.
As the immersive multimedia techniques like Free-viewpoint TV (FTV) develop at an astonishing rate, user's demand for high-quality immersive contents increases dramatically. Unlike traditional uniform artifacts, the distortions within immersive contents could be non-uniform structure-related and thus are challenging for commonly used quality metrics. Recent studies have demonstrated that the representation of visual features can be extracted from multiple levels of the hierarchy. Inspired by the hierarchical representation mechanism in the human visual system (HVS), in this paper, we explore to adopt structural representations to quantitatively measure the impact of such structure-related distortion on perceived quality in FTV scenario. More specifically, a bio-inspired full reference image quality metric is proposed based on 1) low-level contour descriptor; 2) mid-level contour category descriptor; and 3) task-oriented non-natural structure descriptor. The experimental results show that the proposed model outperforms significantly the state-of-the-art metrics.