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Shao, Feng; Li, Kemeng; Lin, Weisi; Jiang, Gangyi; Yu, Mei
IEEE signal processing letters, 2015-Oct., 2015-10-00, Volume: 22, Issue: 10Journal Article
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.
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