Quality Assessment of Stereoscopic Images

By Alexandre Benoit, P. Le Callet, Patrizio Campisi, Romain Cousseau. EURASIP Journal on Image and Video Processing, 2008

406 citations recorded by the source corpus.

Several metrics have been proposed in literature to assess the perceptual quality of two-dimensional images. However, no similar effort has been devoted to quality assessment of stereoscopic images. Therefore, in this paper, we review the different issues related to 3D visualization, and we propose a quality metric for the assessment of stereopairs using the fusion of 2D quality metrics and of the depth information. The proposed metric is evaluated using the SAMVIQ methodology for subjective assessment. Specifically, distortions deriving from coding are taken into account and the quality degradation of the stereopair is estimated by means of subjective tests.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/7915abaa019652627a3b21cdf4ab33d444447caf

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. A. Bovik
2. Anish Mittal
3. Anush K. Moorthy
4. Zhou Wang
5. Lei Zhang
6. Jari Korhonen
7. Xiaokang Yang
8. Guangtao Zhai

In Media Technology

1. A. Bovik
2. Anish Mittal
3. Anush K. Moorthy
4. Zhou Wang
5. Guangtao Zhai
6. Ke Gu
7. Lei Zhang
8. Kede Ma

Citations in the corpus

• Full-reference quality assessment of stereopairs accounting for rivalry (2013, methodology): “Benoit et al. [15] proposed a SSIM-based stereo QA model operating on both stereopairs and disparity maps.”
• Deep learning for objective quality assessment of 3D images (2014, methodology): “The first experiment was done on the “IVC 3D Images Database” [13].”
• Analysis of Public Image and Video Databases for Quality Assessment (2012, background): “• IRCCyN/IVC 3D Image Quality Database [14], [15] was the first public-domain database on 3D image quality.”
• Subjective evaluation of stereoscopic image quality (2013, methodology): “Tables 3 and 4 list the 2D and 3D IQA algorithms evaluated in this study.”