A soft MAP framework for blind super-resolution image reconstruction

Image and Vision Computing

Volumn 27, Issue 4, 2009, Pages 364-373

  He, Yu ^a   Yap, Kim Hui ^a   Chen, Li ^b   Chau, Lap Pui ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b WUHAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Blur identification; Conjugate gradient optimization; Maximum a posteriori estimation; Super resolution

Indexed keywords

CONFORMAL MAPPING; CONJUGATE GRADIENT METHOD; IMAGE PROCESSING; IMAGE RECONSTRUCTION; LARGE SCALE SYSTEMS; OPTICAL RESOLVING POWER; REINFORCEMENT; REPAIR; RESTORATION;

ALTERNATING MINIMIZATIONS; BLUR IDENTIFICATION; BLURRED IMAGES; BLURRING FUNCTIONS; CONJUGATE GRADIENT OPTIMIZATION; HIGH RESOLUTIONS; HR IMAGES; IMAGE FORMATION PROCESSES; ITERATIVE SCHEMES; LIMITED INFORMATIONS; MAXIMUM A POSTERIORI ESTIMATION; NEW ALGORITHMS; SOME APPLICATIONS; SR IMAGE RECONSTRUCTIONS; SUPER-RESOLUTION;

OPTIMIZATION;

EID: 57949110867     PISSN: 02628856     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.imavis.2008.05.010     Document Type: Article

References (34)

1. Zalevsky Z., and Mendlovic D. Optical Superresolution (2004), Springer
2. E. Barrett, D.W. Tyler, P.M. Payton, K. Ip, D.N. Christie, New approaches to image super-resolution beyond the diffraction limit, in: Proceedings of SPIE Conference Unconventional Imaging III, 2007, p. 67120D.
3. S. Borman, R. Stevenson, Spatial resolution enhancement of low resolution image sequences: a comprehensive review with directions for future research, Laboratory Image and Signal Analysis, University of Notre Dame, Technical Report, 1998.
4. Tsai R.Y., and Huang T.S. Multiframe image restoration and registration. Advances in Computer Vision and Image Processing 1 (1984) 317-319
5. P. Vandewalle, S. Susstrunk, A. Vetterli, A frequency domain approach to registration of aliased images with application to super-resolution, EURASIP Journal on Applied Signal Processing, Article ID 71459, 2006.
6. Irani M., and Peleg S. Improving resolution by image registration. CVGIP: Graphical Models and Image Processing 53 (1991) 231-239
7. Elad M., and Feuer A. Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images. IEEE Transactions on Image Processing 6 (1997) 1646-1658
8. Nguyen N., Milanfar P., and Golub G. A computationally efficient superresolution image reconstruction algorithm. IEEE Transactions on Image Processing 10 (2001) 573-583
9. Kim S.P., Bose N.K., and Valenzuela H.M. Recursive reconstruction of high resolution image from noisy undersampled multiframes. IEEE Transactions on Acoustics, Speech, and Signal Processing 38 (1990) 1013-1027
10. Park S.C., Park M.K., and Kang M.G. Super-resolution image reconstruction: a technical overview. IEEE Signal Processing Magazine 20 (2003) 21-36
11. B.C. Tom, A.K. Katsaggelos, N.P. Galatsanos, Reconstruction of a high resolution image from registration and restoration of low resolution images, in: Proceedings of IEEE International Conference on Image Processing, Austin, 1994, pp. 553-557.
12. B.C. Tom, A.K. Katsaggelos, Reconstruction of a high resolution image from multiple degraded mis-registered low resolution images, in: Proceedings of SPIE Conference Visual Communications and Image Processing, Chicago, 1994.
13. B.C. Tom, A.K. Katsaggelos, Multi-channel image identification and restoration using the expectation-maximization algorithm, in: Proceedings of SPIE Conference Applications of Digital Image Processing XVII, San Diego, 1994, pp. 316-331.
14. Schultz R.R., and Stevenson R.L. Extraction of high-resolution frames from video sequences. IEEE Transactions on Image Processing 5 (1996) 996-1011
15. H. Huang, X. Fan, C. Qi, S.-H. Zhu, A learning-based POCS algorithm for face image super-resolution reconstruction, in: Proceedings of International Conference on Machine Learning and Cybernetics, Guangzhou, China, August 2005, pp. 5071-5076.
16. Elad M., and Hel-Or Y. A fast super-resolution reconstruction algorithm for pure translational motion and common space-invariant blur. IEEE Transactions on Image Processing 10 Aug. (2001) 1187-1193
17. N. Nguyen, P. Milanfar, A wavelet-based interpolation-restoration method for superresolution, Invited paper, Circuits, Systems, and Signal Processing, Special issue on advanced signal and image reconstruction, vol. 19, August 2000, pp. 321-338.
18. I. Begin, F.R. Ferrie, Blind super-resolution using a learning-based approach, in: Proceedings of International Conference on Pattern Recognition, Cambridge, United Kingdom, August 2004, pp. 85-89.
19. Nguyen N., Milanfar P., and Golub G. Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement. IEEE Transactions on Image Processing 10 (2001) 1299-1308
20. H. He, L.P. Kondi, A regularization framework for joint blur estimation and super-resolution of video sequences, in: Proceedings of IEEE International Conference on Image Processing, Genova, September 2005, pp. 329-332.
21. Chan T.F., and Chiu-Kwong W. Total variation blind deconvolution. IEEE Transactions on Image Processing 7 (1998) 370-375
22. Farsiu S., Robinson D., Elad M., and Milanfar P. Fast and robust multiframe super resolution. IEEE Transactions on Image Processing 13 (2004) 1327-1344
23. Andrews H.C., and Hunt B.R. Digital Image Restoration (1977), Prentice-Hall, New Jersey
24. He H., and Kondi L.P. Resolution enhancement of video sequences with simultaneous estimation of the regularization parameter. Journal of Electronic Imaging 13 (2004) 586-596
25. S. Baker, T. Kanade, Hallucinating faces, in: Proceedings of International Conference on Automatic Face and Gesture Recognition, Grenoble, France, March 2000, pp. 83-88.
26. Rajan D., and Chaudhuri S. An MRF-based approach to generation of super-resolution images from blurred observations. Journal of Mathematical Imaging and Vision 16 (2002) 5-15
27. Forsythe G.E., Malcolm M.A., and Moler C.B. Computer Methods for Mathematical Computations (1976), Prentice-Hall
28. Foroosh H., Zerubia J.B., and Berthod M. Extension of phase correlation to subpixel registration. IEEE Transactions on Image Processing 11 (2002) 188-200
29. Lee E.S., and Kang M.G. Regularized adaptive high-resolution image reconstruction considering inaccurate subpixel registration. IEEE Transactions on Image Processing 12 (2003) 826-837
30. He H., and Kondi L.P. An image super-resolution algorithm for different error levels per frame. IEEE Transactions on Image Processing 15 (2006) 592-603
31. Sroubek F., and Flusser J. Multichannel blind iterative image restoration. IEEE Transactions on Image Processing 12 (2003) 1094-1106
32. Wang Y., Ostermann J., and Zhang Y.-Q. Video Processing and Communications (2002), Prentice Hall, Upper Saddle River, NJ
33. Sroubek F., and Flusser J. Multichannel blind deconvolution of spatially misaligned images. IEEE Transaction on Image Processing 14 7 (2005) 874-883
34. EI-Khamy S.E., Hadhoud M.M., Dessouky M.I., Salam B.M., and EI-Samle F.E.A. Regularized super-resolution reconstruction of images using wavelet fusion. Optical Engineering 44 (2005)