DocumentCode
2540977
Title
Stereoscopic images quality assessment by jointly evaluating image quality and depth perception
Author
Shao, Feng ; Gu, Shanbo ; Jiang, Gangyi ; Yu, Mei
Author_Institution
Fac. of Inf. Sci. & Eng., Ningbo Univ., Ningbo, China
fYear
2012
fDate
29-31 May 2012
Firstpage
1963
Lastpage
1966
Abstract
Objective quality evaluation of stereoscopic images is useful in three-dimensional television application, and it is difficult to establish a reasonable relationship between objective evaluation and quality score. In this paper, a new stereoscopic image quality assessment method is proposed. In the method, stereoscopic features are first extracted to describe perceptual attributes of image quality and depth perception by singular value decomposition. Then, the relationship between stereoscopic features and quality score is established by using support vector regression. Finally, the objective evaluation values are tested on the symmetric database. Experimental results show that the proposed is more effective in quantifying image quality, compared with other two relevant quality evaluation metrics.
Keywords
feature extraction; regression analysis; singular value decomposition; stereo image processing; support vector machines; visual perception; SVD; SVR; depth perception evaluation; objective quality evaluation; perceptual attributes; quality score; singular value decomposition; stereoscopic feature extraction; stereoscopic image quality assessment; support vector regression; symmetric database; three-dimensional television application; Databases; Feature extraction; Image quality; Measurement; Stereo image processing; Transform coding; Vectors; Objective quality assessment; singular value decomposition (SVD); stereoscopic image; support vector regression (SVR);
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
Conference_Location
Sichuan
Print_ISBN
978-1-4673-0025-4
Type
conf
DOI
10.1109/FSKD.2012.6233721
Filename
6233721
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