Unsupervised feature learning framework for no-reference image quality assessment

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2012, Pages 1098-1105

  Ye, Peng ^a   Kumar, Jayant ^a   Kang, Le ^a   Doermann, David ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CODEBOOKS; COMPUTATIONAL MODEL; DIFFERENT DOMAINS; FEATURE LEARNING; GENERAL PURPOSE; IMAGE ASSESSMENT; IMAGE QUALITY ASSESSMENT; IMAGE REPRESENTATIONS; LOCAL DESCRIPTORS; NO REFERENCES; NO-REFERENCE IMAGE QUALITY ASSESSMENTS; PRIOR KNOWLEDGE; QUALITY ESTIMATION; QUALITY MEASURES; RAW IMAGES; REFERENCE IMAGE; STRUCTURAL SIMILARITY;

ALGORITHMS; COMPUTER VISION; IMAGE CODING;

IMAGE QUALITY;

EID: 84866683924     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2012.6247789     Document Type: Conference Paper

References (29)

1. T. Brandão and M. P. Queluz. No-reference image quality assessment based on DCT domain statistics. Signal Processing, 88:822-833, Apr. 2008.
2. D. Chandler and S. Hemami. VSNR: A wavelet-based visual signal-to-noise ratio for natural images. IEEE Transactions on Image Processing, 16 (9):2284-2298, 2007.
3. A. Coates, B. Carpenter, C. Case, S. Satheesh, B. Suresh, T. Wang, D. J. Wu, and A. Y. Ng. Text detection and character recognition in scene images with unsupervised feature learning. In Intl. Conf. on Document Analysis and Recognition (ICDAR), 2011.
4. A. Coates, H. Lee, and A. Y. Ng. An analysis of single-layer networks in unsupervised feature learning. In In Proceedings of the 14th International Conference on Artificial Intelligence and Statistics (AISTATS), 2011.
5. A. Coates and A. Y. Ng. The importance of encoding versus training with sparse coding and vector quantization. In International Conference on Machine Learning (ICML), pages 921-928, June 2011.
6. E. C. Larson and D. M. Chandler. Most apparent distortion: full-reference image quality assessment and the role of strategy. Journal of Electronic Imaging, 19(1):011006, 2010.
7. C. Li, A. C. Bovik, and X. Wu. Blind image quality assessment using a general regression neural network. IEEE Transactions on Neural Networks, 22(5):793-799, may 2011.
8. Q. Li and Z.Wang. Reduced-reference image quality assessment using divisive normalization-based image representation. IEEE Journal of Selected Topics in Signal Processing, 3(2):202-211, april 2009.
9. C. Liu, W. Freeman, R. Szeliski, and S. B. Kang. Noise estimation from a single image. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), volume 1, pages 901 - 908, 2006.
10. L. Liu, L. Wang, and X. Liu. In defense of soft-assignment coding. In IEEE International Conference on Computer Vision (ICCV), 2011.
11. P. Marziliano, F. Dufaux, S. Winkler, and T. Ebrahimi. Perceptual blur and ringing metrics: application to JPEG2000. Signal Processing: Image Communication, 19(2):163-172, 2004.
12. A. K. Moorthy and A. C. Bovik. Visual importance pooling for image quality assessment. IEEE Journal of Selected Topics in Signal Processing, 3(2):193-201, April 2009.
13. A. K. Moorthy and A. C. Bovik. A two-step framework for constructing blind image quality indices. IEEE Signal Processing Letters, 17(5):513-516, May 2010.
14. A. K. Moorthy and A. C. Bovik. Blind image quality assessment: From natural scene statistics to perceptual quality. IEEE Transactions on Image Processing, 20(12):3350-3364, Dec. 2011.
15. N. Ponomarenko, V. Lukin, A. Zelensky, K. Egiazarian, M. Carli, and F. Battisti. Tid2008 - a database for evaluation of full-reference visual quality assessment metrics. Advances of Modern Radio Electronics, 10:30-45, 2009.
16. R. Raina, A. Battle, H. Lee, B. Packer, and A. Y. Ng. Selftaught learning: transfer learning from unlabeled data. In International conference on Machine learning (ICML), pages 759-766, 2007.
17. M. A. Saad, A. C. Bovik, and C. Charrier. A DCT statisticsbased blind image quality index. IEEE Signal Processing Letters, 17(6):583-586, Jun. 2010.
18. M. A. Saad, A. C. Bovik, and C. Charrier. Model-based blind image quality assessment using natural DCT statistics. IEEE Transactions on Image Processing, 2011 (to appear).
19. H. R. Sheikh and A. C. Bovik. Image information and visual quality. IEEE Transactions on Image Processing, 15(2):430-444, February 2006.
20. H. R. Sheikh, M. F. Sabir, and A. C. Bovik. A statistical evaluation of recent full reference image quality assessment algorithms. IEEE Transactions on Image Processing, 15(11):3440-3451, 2006.
21. H. R. Sheikh, Z. Wang, L. Cormack, and A. C. Bovik. LIVE image quality assessment database release 2. Online, http://live.ece.utexas.edu/research/ quality.
22. H. Tang, N. Joshi, and A. Kapoor. Learning a blind measure of perceptual image quality. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 305 - 312, 2011.
23. H. Tong, M. Li, H. Zhang, C. Zhang, J. He, and W. Ma. Learning no-reference quality metric by examples. In Proceedings of the 11th International Multimedia Modelling Conference, pages 247 - 254, Jan 2005.
24. J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Gong. Locality-constrained linear coding for image classification. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 3360 -3367, june 2010.
25. Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli. Image quality assessment: From error visibility to structural similarity. IEEE Transactions on Image Processing, 13(4):600-612, 2004.
26. Z. Wang, H. R. Sheikh, and A. C. Bovik. No-reference perceptual quality assessment of JPEG compressed images. In IEEE International Conference on Image Processing (ICIP), Rochester, New York, Sep. 22-25 2002.
27. Z. Wang, E. P. Simoncelli, and A. C. Bovik. Multi-scale structural similarity for image quality assessment. Invited Paper, IEEE Asilomar Conference on Signals, Systems and Computers, 2003.
28. J. Yang, K. Yu, Y. Gong, and T. Huang. Linear spatial pyramid matching using sparse coding for image classification. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1794 -1801, 2009.
29. P. Ye and D. Doermann. No-reference image quality assessment based on visual codebook. In IEEE International Conference on Image Processing (ICIP), 2011.