Fast and stable Bayesian image expansion using sparse edge priors

IEEE Transactions on Image Processing

Volumn 16, Issue 4, 2007, Pages 1073-1084

  Raj, Ashish ^a   Thakur, Kailash ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b CALLAGHAN INNOVATION   (New Zealand)

Author keywords

Bayesian estimation; Edge driven priors; Image expansion; Interpolation; Subspace separation

Indexed keywords

ALGORITHMS; FOURIER TRANSFORMS; INTERPOLATION; MATRIX ALGEBRA;

BAYESIAN ESTIMATION; IMAGE EXPANSION; MAXIMUM A POSTERIORI;

IMAGE PROCESSING;

ALGORITHM; ARTICLE; ARTIFACT; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFACTS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 34047200699     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2006.891339     Document Type: Article

References (36)

1. E. Meijering, "A chronology of interpolation," Proc. IEEE, vol. 90, no. 3, pp. 319-342, Mar., 2002.
2. S. Andrews and F. Harris, "Polynomial approximations of interpolants," in Proc. 33rd Asilomar Conf. Signals, Systems, and Computers, 1999, vol. 1, pp. 447-451.
3. T. Blu, P. Thvenaz, and M. Unser, "Interpolation revisited," IEEE Trans. Med. Imag., vol. 19, no. 7, pp. 739-758, Jul. 2000.
4. R. G. Keys, "Cubic convolution interpolation for digital image processing," IEEE Trans. Acoust., Speech, Signal Process., vol. ASSP-29, no. 6, pp. 1153-1160, Dec. 1981.
5. L. Condat, T. Blu, and M. Unser, "Beyond interpolation: Optimal reconstruction by quasi-interpolation," in Proc. IEEE Int. Conf. Image Processing, 2005, pp. 33-36.
6. S. Lee and J. Paik, "Image interpolation using adaptive fast b-spline filtering," in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing, 1993, pp. 177-180.
7. K. Ratakonda and N. Ahuja, "POCS-based adaptive image magnification," in Proc. IEEE Int. Conf. Image Processing, Oct. 1998, vol. 3, pp. 203-207.
8. K. Jensen and D. Anastassiou, "Subpixel edge localization and the interpolation of still images," IEEE Trans. Image Process., vol. 4, no. 3, pp. 285-295, Mar. 1995.
9. J. Allebach and P.Wong, "Edge-directed interpolation," in Proc. IEEE Int. Conf. Image Processing, 1996, pp. 707-710.
10. G. Ramponi, "Warped distance for space-variant linear image interpolation," IEEE Trans. Image Process., vol. 8, no. 5, pp. 629-639, May 1999.
11. X. Li and M. Orchard, "New edge directed interpolation," IEEE Trans. Image Process., vol. 10, no. 10, pp. 1521-1527, Oct. 2001.
12. S. Citrin and M. R. Azimi-Sadjadi, "A full-plane block kalman filter for image restoration," IEEE Trans. Image Process., vol. 1, no. 4, pp. 488-495, Apr. 1992.
13. K. Erler and E. Jernigan, "Adaptive recursive image filtering," Proc. SPIE, pp. 3017-3021, 1991.
14. D. Muresan and T. Parks, "Adaptive optimal recovery image interpolation," IEEE Trans. Image Process., vol. 13, no. 5, pp. 690-698, May 2004.
15. R. Schultz and R. Stevenson, "A Bayesian approach to image expansion for improved definition," IEEE Trans. Image Process., vol. 3, no. 3, pp. 233-242, May 1994.
16. R. Chan, T. Chan, L. Shen, and Z. Shen, "Wavelet algorithms for high-resolution image reconstruction," SIAM J. Sci. Comput., vol. 24, no. 4, pp. 1408-1432, 2003.
17. R. Molina, M. Vega, J. Abad, and A. Katsaggelos, "Parameter estimation in bayesian high-resolution image reconstruction with multisensors," IEEE Trans. Image Process., vol. 12, no. 12, pp. 1655-1667, Dec. 2003.
18. M. Elad and A. Feuer, "Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images," IEEE Trans. Image Process., vol. 6, no. 12, pp. 1646-1658, Dec. 1997.
19. N. Bose and K. Boo, "High-resolution image reconstruction with multisensors," Int. J. Imag. Sci. Technol., vol. 9, pp. 141-163, 1998.
20. H. A. Aly and E. Dubois, "Specification of the observation model for regularized image up-sampling," IEEE Trans. Image Process., vol. 14, no. 5, pp. 567-576, May 2005.
21. T. Berber, J. Stromberg, and T. Eltoft, "Adaptive regularized constrained least squares image restoration," IEEE Trans. Image Process., vol. 8, no. 9, pp. 1191-1203, Sep. 1999.
22. A. Katsaggelos, J. Biermond, R. Schafer, and R. Mersereau, "A regularized iterative image restoration algorithm," IEEE Trans. Signal Process., vol. 39, no. 4, pp. 914-929, Apr. 1991.
23. S. Li, Markov Random Field Modeling in Computer Vision. New York: Springer-Verlag, 1995.
24. V. Z. Mesarovic, N. P. Galatsanos, and M. N.Wernick, "Iterative maximum a posteriori (MAP) restoration from partially-known blur for tomographic reconstruction," in Proc. IEEE Int. Conf. Image Processing, 1995, pp. 512-515.
25. J. Canny, "A computational approach to edge detection," IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-8, no. 6, pp. 679-698, Nov. 1986.
26. G. Borgefors, "Hierarchical chamfer matching: A parametric edge matching algorithm," IEEE Trans. Pattern Anal. Mach. Intell., vol. 10, no. 6, pp. 849-865, Nov. 1988.
27. C. Bouman and K. Sauer, "A generalized Gaussian image model for edge preserving MAP estimation," IEEE Trans. Image Process., vol. 2, no. 3, pp. 296-310, Jul. 1993.
28. D. W. Paglieroni, "Distance transforms: Properties and machine vision applications," Comput. Vis., Graph., Image Process.: Graph. Models Image Process., vol. 54, no. 1, pp. 56-74, 1992.
29. A. Thompson, J. Brown, J. Kay, and M. Titterington, "A study of methods for choosing the smoothing parameter in image restoration by regularization," IEEE Trans. Pattern Anal. Mach. Intell., vol. 13, no. 5, pp. 326-339, May 1991.
30. M. Chen and T. Pavlidis, "Image seaming for segmentation on parallel architecture," IEEE Trans. Pattern Anal. Mach. Intell., vol. 12, no. 6, pp. 588-594, Jun. 1990.
31. R. M. Gray, Toeplitz and Circulant Matrices: A Review. Boston, MA: Now Publishers, 2006.
32. G. Golub and C. Van Loan, Matrix Computations. Baltimore, MD: Johns Hopkins Univ. Press, 1996.
33. Altamira, Commercial, Fractal Based Interpolation Algorithm [Online]. Available: http://www.genuinefractals.com
34. D. Muresan and T. Parks, "Adaptive optimal recovery image interpolation," in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing, 2001, pp. 1949-1952.
35. W. Freeman, T. Jones, and E. Pasztor, "Example-based super-resolution," IEEE Comput. Graph. Appl., vol. 22, no. 2, pp. 56-65, Mar./Apr. 2002.
36. A. Raj and R. Zabih, "A graph cut algorithm for generalized image deconvolution," in Proc. Int. Conf. Computer Vision, 2005, pp. 1901-1909.