TY - GEN
T1 - Using 3D structural tensors in quality evaluation of stereoscopic video
AU - Appuhami, Harsha D.
AU - Martini, Maria G.
AU - Hewage, Chaminda T.E.R.
N1 - Publisher Copyright:
© 2014 IEEE.. © 2014 IEEE.
PY - 2015/3/2
Y1 - 2015/3/2
N2 - Recent advancements in 3D imaging, coding, compression, storage, transmission, and error concealment techniques enable wide usage of 3D video/image applications. Video quality assessment plays a major role in improving the perceived quality at the receiver side, since such information can be used at the transmitter or in the different network nodes for system optimization 'on-the-fly'. Most of the objective quality metrics in use are Full-Reference (FR), requiring the original video sequance for comparison. In the case of quality assessment for stereoscopic video, both left and right views need to be considered. In this paper, we introduce a novel Reduced-Reference (RR) quality metric for stereoscopic video using 3D structural tensors, based on the fact that the Human Visual System (HVS) is more sensitive to the structural information present in the scene. This method incorporates a new saliency detection method by considering spatial and temporal aspects of the video sequance. The Correlation Coefficient (CC) calculated for the obtained results shows that the values of the derived metric are well correlated with the corresponding subjective test results.
AB - Recent advancements in 3D imaging, coding, compression, storage, transmission, and error concealment techniques enable wide usage of 3D video/image applications. Video quality assessment plays a major role in improving the perceived quality at the receiver side, since such information can be used at the transmitter or in the different network nodes for system optimization 'on-the-fly'. Most of the objective quality metrics in use are Full-Reference (FR), requiring the original video sequance for comparison. In the case of quality assessment for stereoscopic video, both left and right views need to be considered. In this paper, we introduce a novel Reduced-Reference (RR) quality metric for stereoscopic video using 3D structural tensors, based on the fact that the Human Visual System (HVS) is more sensitive to the structural information present in the scene. This method incorporates a new saliency detection method by considering spatial and temporal aspects of the video sequance. The Correlation Coefficient (CC) calculated for the obtained results shows that the values of the derived metric are well correlated with the corresponding subjective test results.
KW - 3D Structural Tensors
KW - Eigenvalue
KW - Eigenvector
KW - Quality of Experience
KW - Quaternion Fourier Transform
KW - Stereoscopic Video
UR - https://www.scopus.com/pages/publications/84925438747
U2 - 10.1109/VCIP.2014.7051595
DO - 10.1109/VCIP.2014.7051595
M3 - Conference contribution
AN - SCOPUS:84925438747
T3 - 2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014
SP - 418
EP - 421
BT - 2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014
Y2 - 7 December 2014 through 10 December 2014
ER -