IEEE Journal of Selected Topics in Signal Processing · 2011 · 216 citations · 35 references
ArchitectureVisualizationDigital RenderingRenderingVisual Perception3D Imaging3D RenderingImage QualityImage SynthesisImage-based RenderingThree-dimensional PerceptionDepth Image-based RenderingDistortionsPerceptual Quality AssessmentQuality Metric DevelopmentSubjective Quality AssessmentView QualityView SynthesisVisual Quality Degradation
3DTV technology has brought out new challenges such as the question of synthesized views evaluation. Synthesized views are generated through a depth image-based rendering (DIBR) process. This process induces new types of artifacts whose impact on visual quality has to be identified considering various contexts of use. While visual quality assessment has been the subject of many studies in the last 20 years, there are still some unanswered questions regarding new technological improvement. DIBR is bringing new challenges mainly because it deals with geometric distortions. This paper considers the DIBR-based synthesized view evaluation problem. Different experiments have been carried out. They question the protocols of subjective assessment and the reliability of the objective quality metrics in the context of 3DTV, in these specific conditions (DIBR-based synthesized views), and they consist in assessing seven different view synthesis algorithms through subjective and objective measurements. Results show that usual metrics are not sufficient for assessing 3-D synthesized views, since they do not correctly render human judgment. Synthesized views contain specific artifacts located around the disoccluded areas, but usual metrics seem to be unable to express the degree of annoyance perceived in the whole image. This study provides hints for a new objective measure. Two approaches are proposed: the first one is based on the analysis of the shifts of the contours of the synthesized view; the second one is based on the computation of a mean SSIM score of the disoccluded areas.
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C. Bovik, Hamid R. Sheikh et al. · IEEE Transactions on Image Processing · 2004 · 56K citations
A universal image quality index
Zhou Wang, Alan C. Bovik · IEEE Signal Processing Letters · 2002 · 5.7K citations