Stereoscopic video quality assessment based on visual attention and just-noticeable difference models. Issue 4 (April 2016)

• Record Type: Journal Article
• Authors: Qi, Feng; Zhao, Debin; Fan, Xiaopeng; Jiang, Tingting
• Is Part Of: Signal, image and video processing. Volume 10:Issue 4(2016)
• Page Start: 737
• Page End: 744
• Publication Date: 2016-04
• Subjects: Stereoscopic video quality assessment -- Just-noticeable difference -- Stereoscopic visual attention -- Binocular masking; Signal processing -- Digital techniques -- Periodicals; Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; 621.3822
• DOI: 10.1007/s11760-015-0802-4
• Languages: English
• ISSNs: 1863-1703

Abstract

Abstract With the consideration that incorporating visual saliency information appropriately can benefit image quality assessment metrics, this paper proposes an objective stereoscopic video quality assessment (SVQA) metric by incorporating stereoscopic visual attention (SVA) to SVQA metric. Specifically, based upon the multiple visual masking characteristics of HVS, a stereoscopic just-noticeable difference model is proposed to compute the perceptual visibility for stereoscopic video. Next, a novel SVA model is proposed to extract stereoscopic visual saliency information. Then, the quality maps are calculated by the similarity of the original and distorted stereoscopic videos' perceptual visibility. Finally, the quality score is obtained by incorporating visual saliency information to the pooling of quality maps. To evaluate the proposed SVQA metric, a subjective experiment is conducted. The experimental result shows that the proposed SVQA metric achieves better performance in comparison with the existing SVQA metrics.