DocumentCode :
105259
Title :
Using Binocular Feature Combination for Blind Quality Assessment of Stereoscopic Images
Author :
Feng Shao ; Kemeng Li ; Weisi Lin ; Gangyi Jiang ; Mei Yu
Author_Institution :
Fac. of Inf. Sci. & Eng., Ningbo Univ., Ningbo, China
Volume :
22
Issue :
10
fYear :
2015
fDate :
Oct. 2015
Firstpage :
1548
Lastpage :
1551
Abstract :
The quality assessment of 3D images is more challenging than its 2D counterparts, and little investigation has been dedicated to blind quality assessment of stereoscopic images. In this letter, we propose a novel blind quality assessment for stereoscopic images based on binocular feature combination. The prominent contribution of this work is that we simplify the process of binocular quality prediction as monocular feature encoding and binocular feature combination. Experimental results on two publicly available 3D image quality assessment databases demonstrate the promising performance of the proposed method.
Keywords :
feature extraction; image coding; stereo image processing; 3D image quality assessment; binocular feature combination; binocular quality prediction; monocular feature encoding; stereoscopic image blind quality assessment; Feature extraction; Measurement; Quality assessment; Solid modeling; Stereo image processing; Three-dimensional displays; Vectors; Binocular feature combination; blind image quality assessment; stereoscopic image; support vector regression;
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2015.2413946
Filename :
7062011
Link To Document :
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