Robust and computationally efficient superresolution algorithm

Journal of the Optical Society of America A: Optics and Image Science, and Vision

Volumn 24, Issue 4, 2007, Pages 984-992

  Suresh, Kaggere V ^a   Rajagopalan, Ambasamudram N ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

Author keywords

[No Author keywords available]

Indexed keywords

ERROR ANALYSIS; MARKOV PROCESSES; MATHEMATICAL MODELS; MOTION ESTIMATION; PIXELS;

BLURRING; ITERATED CONDITIONAL MODES; MARKOV RANDOM FIELD; SUPERRESOLUTION; WARPING;

IMAGE RESOLUTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 34248391476     PISSN: 10847529     EISSN: None     Source Type: Journal    
DOI: 10.1364/JOSAA.24.000984     Document Type: Article

References (25)

1. S. Borman and R. L. Stevenson, "Super-resolution from image sequences - a review," in Proceedings of 1998 Midwest Symposium on Circuits and Systems (Institute of Electrical and Electronics Engineers, 1998), pp. 374-378.
2. S. Chaudhuri, Super-Resolution Imaging (Kluwer, 2001).
3. M. G. Kang and S. Chaudhuri, "Super-resolution image reconstruction," IEEE Signal Process. Mag. 20, 21-36 (2003).
4. S. Farsiu, D. Robinson, M. Elad, and P. Mílanfar, "Advances and challenges in super-resolution," Int. J. Imaging Syst. Technol. 14, 47-57 (2004).
5. M. Elad and A. Feuer, "Restoration of a single super-resolution image from several blurred, noisy and under-sampled measured images," IEEE Trans. Image Process. 6, 1646-1658 (1997).
6. D. Rajan and S. Chaudhuri, "Generation of super-resolution images from blurred observations using Markov random fields," in Proceedings of the IEEE Conference on Acoustics, Speech, and Signal Processing (Institute of Electrical and Electronics Engineers, 2001), pp. 1837-1840.
7. A. N. Rajagopalan and V. P. Kiran, "Motion-free super-resolution and the role of relative blur," J. Opt. Soc. Am. A 20, 2022-2032 (2003).
8. N. K. Bose, M. K. Ng, and A. C. Yau, "A fast algorithm for image super-resolution from blurred observations," EURASIP J. Appl. Signal Process 2006, 35726 (2006).
9. S. Baker and T. Kanade, "Limits on super-resolution and how to break them," IEEE Trans. Pattern Anal. Mach. Intell. 24, 1167-1183 (2002).
10. Q. Wang, X. Tang, and H. Shum, "Patch-based blind super-resolution," in Proceedings of the IEEE International Conference on Computer Vision (IEEE, 2005), pp. 709-716.
11. T. S. Huang and R. Y. Tsai, "Multiframe image restoration and registration," in Advances in Computer Vision and Image Processing, T. S. Huang, ed. (JAI Press, 1984), Vol. 1, pp. 317-339.
12. S. P. Kim, N. K. Bose, and H. M. Valenzuela, "Recursive reconstruction of high resolution image from noisy under-sampled multiframes," IEEE Trans. Acoust., Speech, Signal Process. 38, 1013-1027 (1990).
13. H. Ur and D. Gross, "Improved resolution from sub-pixel shifted pictures," CVGIP: Graph. Models Image Process. 54, 181-186 (1992).
14. D. Keren, S. Peleg, and R. Brada, "Image sequence enhancement using sub-pixel displacements," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Institute of Electrical and Electronics Engineers, 1988), pp. 742-746.
15. S. Peleg and M. Irani, "Improving resolution by image registration," CVGIP: Graph. Models Image Process. 53, 231-239 (1991).
16. R. L. Stevenson and R. R. Schultz, "Extraction of high-resolution frames from video sequences," IEEE Trans. Image Process. 5, 996-1011 (1996).
17. R. C. Hardie, K. Barnard, and E. E. Armstrong, "Joint MAP registration and high-resolution image estimation using a sequence of under-sampled images," IEEE Trans. Image Process. 6, 1621-1632 (1997).
18. A. Zomet, A. Rav-Acha, and S. Peleg, "Robust super-resolution," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Institute of Electrical and Electronics Engineers, 2001), pp. 645-650.
19. E. S. Lee and M. G. Kang, "Regularized adaptive high-resolution image reconstruction considering inaccurate sub-pixel registration," IEEE Trans. Image Process. 12, 826-837 (2003).
20. S. Farsiu, M. D. Robinson, M. Elad, and R. Milanfar, "Fast and robust multiframe super resolution," IEEE Trans. Image Process. 13, 1327-1344 (2004).
21. S. Z. Li, Markov Random Field Modeling in Computer Vision (Springer-Verlag, 1995).
22. J. Besag, "On the statistical analysis of dirty pictures," J. R. Stat. Soc. Ser. B (Methodol.) 48, 259-302 (1986).
23. S. Chaudhuri and A. N. Rajagopalan, Depth from Defocus: A Real Aperture Imaging Approach (Springer-Verlag, 1999).
24. S. Geman and D. Geman, "Stochastic relaxation, Gibbs distribution and the Bayesian restoration of images," IEEE Trans. Image Process. 6, 721-741 (1984).
25. A. Zomet and S. Peleg, "Super-resolution from multiple images having arbitrary mutual motion," in Super-Resolution Imaging, S. Chaudhuri, ed. (Kluwer, 2001), pp. 195-209.