FUZZY LOGIC AND TEMPORAL INFORMATION APPLIED TO VIDEO QUALITY ASSESSMENT
Keywords:
Objective Video Quality Assessment, Structural Similarity Index, Fuzzy Logic, Visual Attention, Temporal AnalysisAbstract
Video Quality Assessment (VQA) plays an important role for video communications systems and services, mainly to determine, accurately, the ratio between the provided quality and the resource demand. The objective VQA is a fast and viable methodology to determine the video quality for video service providers, although it presents an unsat- isfactory correlation with the scores of quality given by the Human Visual System (HVS). The authors propose a novel full reference objective video quality metric considering spa- tial and temporal analysis. The spatial analysis used an algorithm, based on fuzzy logic, to classify the regions in three components. Temporal analysis was performed by means of the perceptual weighted structural similarity index (PW-SSIM) between the frames that contained the dierences of pixels in the same spatial position and in subsequent frames. To validate the proposed VQA algorithm, the correlation coecients between the objective measures and the subjective scores provided by the LIVE Video Quality Database were computed, considering the following distortions: H.264 and MPEG-2 en- coding and transmission of H.264 bit-streams over IP and wireless networks. The results demonstrate that the proposed algorithm is a competitive alternative when compared with the classical objective algorithms such as MOVIE.
Downloads
References
Z. Wang and Q. Li, Information content weighting for perceptual image quality assessment,"
Image Processing, IEEE Transactions on, vol. 20, no. 5, pp. 1185 {1198, may 2011.
M. Farias and W. Akamine, On performance of image quality metrics enhanced with visual
attention computational models," Electronics Letters, vol. 48, no. 11, pp. 631 {633, 24 2012.
J. Li, G. Chen, Z. Chi, and C. Lu, Image coding quality assessment using fuzzy integrals with
a three-component image model," IEEE Transactions on Fuzzy Systems, vol. 12, no. 1, pp. 99 {
, feb. 2004.
C. Li and A. C. Bovik, Content-weighted video quality assessment using a three-component image
model," J. Electronic Imaging, vol. 19, no. 1, p. 011003, 2010.
K. Seshadrinathan, R. Soundararajan, A. C. Bovik, and L. K. Cormack, A subjective study to
evaluate video quality assessment algorithms," SPIE Proceedings Human Vision and Electronic
Imaging, 2010.
||, Study of subjective and objective quality assessment of video," IEEE Transactions on
Image Processing, pp. 1427{1441, 2010.
M. Corbetta, Frontoparietal cortical networks for directing attention and the eye to visual locations:
Identical, independent, or overlapping neural systems?" Proceedings of the National Academy
of Sciences USA, vol. 95, pp. 831 { 838, 1998.
C. D. M. Regis, J. V. M. Cardoso, and M. S. Alencar, E ect of visual attention areas on the
objective video quality assessment," in Proceedings of 18th Brazilian Symposium on Multimedia
and the Web (WebMedia'12), October 2012.
X. Ran and N. Farvardin, A perceptually motivated three-component image model-part i: description
of the model," IEEE Transactions on Image Processing, vol. 4, no. 4, pp. 401 {415, apr
C. Li and A. C. Bovik, Content-partitioned structural similarity index for image quality
assessment," Image Communications, vol. 25, no. 7, pp. 517{526, Aug. 2010. [Online]. Available:
http://dx.doi.org/10.1016/j.image.2010.03.004
S. Gu, F. Shao, G. Jiang, and M. Yu, A new four-component gradient-based structural similarity
metric using adaptive weights," in Eighth International Conference on Fuzzy Systems and
Knowledge Discovery (FSKD), vol. 2, july 2011, pp. 970 {973.
C. D. M. Regis, J. V. M. Cardoso, I. P. Oliveira, and M. S. Alencar, Performance of the objective
video quality metrics with perceptual weighting considering rst and second order di erential operators,"
in Proceedings of 18th Brazilian Symposium on Multimedia and the Web (WebMedia'12),
October 2012.
ITU-T, ITU-T recommendation P.910, subjective video quality assessment methods for multimedia
applications," April 2008.
C. Vu and S. Deshpande, Vimssim: from image to video quality assessment," in Proceedings of
the 4th Workshop on Mobile Video, ser. MoVid '12. New York, NY, USA: ACM, 2012, pp. 1{6.
[Online]. Available: http://doi.acm.org/10.1145/2151677.2151679
M. Narwaria, W. Lin, and A. Liu, Low-complexity video quality assessment using temporal
quality variations," IEEE Transactions on Multimedia, vol. 14, no. 3, pp. 525 {535, june 2012.
R. C. Gonzalez and R. E. Woods, Digital Image Processing (3rd Edition). Upper Saddle River,
NJ, USA: Prentice-Hall, Inc., 2006.
J. Yen and R. Langari, Fuzzy Logic: Intelligence, Control and Information. Prentice-Hall, 1999.
L. A. Zadeh, Fuzzy sets," Information and Control, vol. 8, pp. 338{353, 1965.
C. D. M. Regis, J. V. M. Cardoso, and M. S. Alencar, Video quality assessment based on the
e ect of the estimation of the spatial perceptual information," in Proceedings of XXX Brazilian
Symposium of Telecommunications (SBrT'12), 2012.
T. Brand~ao and M. Queluz, No-reference quality assessment of h.264/avc encoded video," IEEE
Transactions on Circuits and Systems for Video Technology, vol. 20, no. 11, pp. 1437 {1447, nov.
VQEG, Final report from the video quality experts group on the validation of objective models
of video quality assessment, phase II (fr-tv2," April 2000, available at http://www.vqeg.org/.
Z. Wang, A. C. Bovik, H. R. Sheikh, S. Member, and E. P. Simoncelli, Image quality assessment:
From error measurement to structural similarity," IEEE Transactions on Image Processing, vol. 13,
pp. 600{612, 2004.
Z. Wang, E. P. Simoncelli, and A. C. Bovik, Multi-scale structural similarity for image quality
assessment," in Proceedings of IEEE Asilomar Conference on Signals, Systems, and Computers,
, pp. 1398{1402.
D. M. Chandler and S. S. Hemami, Vsnr: A wavelet-based visual signal-to-noise ratio for natural
images." IEEE Transactions on Image Processing, vol. 16, no. 9, pp. 2284{2298, 2007.
H. R. Sheikh and A. C. Bovik, Image information and visual quality," in IEEE Transactions on
Image Processing, 2004, pp. 430{444.
K. Seshadrinathan and A. Bovik, Motion tuned spatio-temporal quality assessment of natural
videos," Image Processing, IEEE Transactions on, vol. 19, no. 2, pp. 335 {350, feb. 2010.
