Objective image quality assessment based on support vector regression

IEEE Transactions on Neural Networks

Volumn 21, Issue 3, 2010, Pages 515-519

  Narwaria, Manish ^a   Lin, Weisi ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Image quality assessment; Image structure; Singular value decomposition (SVD); Support vector regression (SVR)

Indexed keywords

AUTOMATIC PREDICTION; COMPLEX DATA; FEATURE SELECTION; HUMAN PERCEPTION; HUMAN VISUAL SYSTEMS; IMAGE QUALITY ASSESSMENT; IMAGE STRUCTURES; IN-LINE; MACHINE-LEARNING; MODEL PARAMETERS; NEW APPROACHES; OBJECTIVE IMAGE QUALITY; OBJECTIVE IMAGE QUALITY ASSESSMENT; SINGULAR VECTORS; STRUCTURAL CHANGE; STRUCTURAL INFORMATION; SUPPORT VECTOR REGRESSIONS; VISUAL PROCESSING SYSTEMS; VISUAL QUALITIES;

FEATURE EXTRACTION; IMAGE ANALYSIS; IMAGE QUALITY; REGRESSION ANALYSIS; VECTORS; VISUAL COMMUNICATION;

SINGULAR VALUE DECOMPOSITION;

ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; HUMAN; IMAGE PROCESSING; INFORMATION RETRIEVAL; METHODOLOGY; PHYSIOLOGY; REPRODUCIBILITY; VISUAL SYSTEM;

ARTIFICIAL INTELLIGENCE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; VISUAL PATHWAYS;

EID: 77649273216     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2010.2040192     Document Type: Article

References (19)

1. Z. Wang and A. C. Bovik, Modern Image Quality Assessment. San Rafael, CA: Morgan & Claypool, 2006.
2. P. Barten, Contrast Sensitivity of the Human Eye and Its Effects on Image Quality. Pittsburgh, PA: SPIE, 1999.
3. D. M. Rouse and S. S. Hemami, "Analyzing the role of visual structure in the recognition of natural image content with multi-scale SSIM," in Proc. Western New York Image Process. Workshop, Oct. 2007.
4. Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: From error measurement to structural similarity," IEEE Trans. Image Process., vol. 13, no. 4, pp. 600-612, Apr. 2004.
5. W. Lin, L. Dong, and P. Xue, "Visual distortion gauge based on discrimination of noticeable contrast changes," IEEE Trans. Circuits Syst. Video Technol., vol. 15, no. 7, pp. 900-909, Jul. 2005.
6. A. Blum and P. Langley, "Selection of relevant features and examples in machine learning," Artif. Intell., vol. 97, no. 1-2, pp. 245-271, 1997.
7. M. P. Eckert and A. P. Bradley, "Perceptual quality metrics applied to still image compression," Signal Process., vol. 70, pp. 177-200, 1998.
8. P. Gastaldo, S. Rovetta, and R. Zunino, "Objective quality assessment of MPEG-2 video streams by using CBP neural networks," IEEE Trans. Neural Netw., vol. 13, no. 4, pp. 939-947, Jul. 2002.
9. P. L. Callet, V. G. Christian, and B. Dominique, "A convolutional neural network approach for objective video quality assessment," IEEE Trans. Neural Netw., vol. 17, no. 5, pp. 1316-1327, Sep. 2006.
10. A. Bouzerdoum, A. Havstad, and A. Beghdadi, "Image quality assessment using a neural network approach," in Proc. 4th IEEE Int. Symp. Signal Process. Inf. Technol., 2004, pp. 330-333.
11. P. Carrai, I. Heynderickz, P. Gastaldo, R. Zunino, and P. R. Monza, "Image quality assessment by using neural networks," in Proc. IEEE Int. Symp. Circuits Syst., vol. 5, pp. 253-256.
12. G. W. Stewart, "Stochastic perturbation theory," SIAM Rev., vol. 32, no. 4, pp. 579-610, 1990.
13. A. M. Eskicioglu, A. Gusev, and A. Shnayderman, "An SVD-based gray-scale image quality measure for local and global assessment," IEEE Trans. Image Process., vol. 15, no. 2, pp. 422-429, Feb. 2006.
14. Schölkopf and A. J. Smola, Learning With Kernels. Cambridge, MA: MIT Press, 2002.
15. D. M. Chandler and S. S. Hemami, "VSNR: A wavelet-based visual signal-to-noise ratio for natural images," IEEE Trans. Image Process., vol. 16, no. 9, pp. 2284-2298, Sep. 2007.
16. H. R. Sheikh, Z. Wang, A. C. Bovik, and L. K. Cormack, "Image and video quality assessment research at LIVE," [Online]. Available: http://live.ece.utexas.edu/research/quality
17. P. Le Callet, "Florent Autrusseau subjective quality assessment IRCCyN/IVC database," [Online]. Available: http://www2.irccyn.ec-nantes.fr/ ivcdb
18. A. M. Rohaly, J. Libert, P. Corriveau, and A. Webster, Eds., "Final report from the video quality experts group on the validation of objective models of video quality assessment," Mar. 2000 [Online]. Available: www.vqeg.org
19. Y. Horita, Y. Kawayoke, and Z. M. P. Sazzad, "Image quality evaluation database," [Online]. Available: http://160.26.142.130/toyama- database.zip