Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time

IEEE Transactions on Image Processing

Volumn 6, Issue 8, 1997, Pages 1064-1076

  Patti, Andrew J ^a,b   Sezan, M Ibrahim ^a,c   Tekalp, A Murat ^a,d  

^a IEEE   (United States)

^b HEWLETT PACKARD LABORATORIES   (United States)

^c SHARP LABORATORIES OF AMERICA   (United States)

^d UNIVERSITY OF ROCHESTER   (United States)

Author keywords

Standards conversion; Superresolution; Video resampling; Video stills

Indexed keywords

ADAPTIVE ALGORITHMS; HIGH DEFINITION TELEVISION; INTERPOLATION; MATHEMATICAL MODELS; TELEVISION STANDARDS; VIDEO CAMERAS; VIDEO SIGNAL PROCESSING;

LOW RESOLUTION (LR) CAMERA SYSTEMS; SAMPLING LATTICES; SUPERRESOLUTION VIDEO RECONSTRUCTION;

IMAGE RECONSTRUCTION;

EID: 0031211153     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/83.605404     Document Type: Article

References (25)

1. M. Bierling, "Displacement estimation by hierarchical blockmatching," in Proc. SPIE Visual Communications and Image Processing '88, pp. 942-951.
2. G. Wolberg, Digital Image Warping. Los Alamitos, CA: IEEE Comput. Soc. Press, 1990.
3. J. Bergen, P. Burt, R. Hingorani, and S. Peleg, "A three-frame algorithm for estimating two-component image motion," IEEE Trans. Pattern Anal. Machine Intell., vol. 14, pp. 886-896, Sept. 1992.
4. A. M. Tekalp, M. K. Ozkan, and M. I. Sezan, "High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration," in IEEE Int. Conf. Acoustics, Speech, Signal Processing, San Francisco, CA, Mar. 23-26, 1992, pp. III-169-172.
5. H. Ur and D. Gross, "Improved resolution form subpixel shifted pictures," CVGIP: Graph. Models Image Processing, vol. 54, pp. 181-186, Mar. 1992.
6. R. Y. Tsai and T. S. Huang, "Multiframe image restoration and registration," in Advances in Computer Vision and Image Processing, T. S. Huang, Ed. Greenwich, CT: JAI Press, 1984.
7. S. P. Kim, N. K. Bose, and H. M. Valenzuela, "Recursive reconstruction of high resolution image from noisy undersampled multiframes," IEEE Trans. Acoust., Speech Signal Processing, vol. 38, pp. 1013-1027, June 1990.
8. S. P. Kim and W.-Y. Su, "Recursive high-resolution reconstruction of blurred multiframe images," IEEE Trans. Image Processing, vol. 2, pp. 534-539, Oct. 1993.
9. B. C. Tom, A. K. Katsaggelos, and N. P. Galatsanos, "Reconstruction of a high resolution image from registration and restoration of low resolution images," in Proc. IEEE Int. Conf. Image Processing, Austin, TX, Nov. 13-16, 1994.
10. H. Stark and P. Oskoui, "High-resolution image recovery from image-plane arrays, using convex projections," J. Opt. Soc. Amer. A, vol. 6, pp. 1715-1726, 1989.
11. M. Irani and S. Peleg, "Improving resolution by image registration," CVGIP: Graph. Models Image Processing, vol. 53, pp. 231-239, May 1991.
12. M. R. Civanlar and H. J. Trussell, "The Landweber iteration and projection onto convex sets," IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-33, pp. 1632-1634, Dec. 1985.
13. S. Mann and R. W. Picard, "Virtual bellows: constructing high quality stills from video," in Proc. IEEE Int. Conf. Image Processing, Austin, TX, Nov. 13-16, 1994.
14. M. Irani and S. Peleg, "Motion analysis for image enhancement: Resolution, occlusion, and transparency," J. Visual Commun. Image Represent., vol. 4, pp. 324-335, Dec. 1993.
15. A. J. Patti, "Digital video filtering for standards conversion and resolution enhancement," Ph.D. dissertation, Univ. Rochester, Rochester, NY, 1995.
16. T. Komatsu, K. Aizawa, T. Igarashi, and T. Saito, "Signal-processing based method for acquiring very high resolution images with multiple cameras and its theoretical analysis," Proc. Inst. Electr. Eng. - I, vol. 140, pp. 19-25, Feb. 1993.
17. T. Komatsu, T. Igarashi, K. Aizawa, and T. Saito, "Very high resolution imaging sheme with multiple different-aperature cameras," Signal Processing: Image Commun., vol. 5, pp. 511-526, Dec. 1993.
18. P. Cheeseman, B. Kanefsky, and R. Hanson, "Super-resolved surface reconstruction from multiple images," Tech. Rep., NASA, Jan. 1993.
19. R. R. Schultz and R. L. Stevenson, "A Bayesian approach to image expansion for improved definition," IEEE Trans. Image Processing, vol. 3, pp. 233-242, May 1994.
20. R. R. Schultz and R. L. Stevenson, "Improved definition video frame enhancement," in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, Detroit, MI, May 1995, pp. 2169-2172.
21. H. J. Trussell and S. Fogel, "Identification and restoration of spatially variant motion blurs in sequential images," IEEE Trans. Image Processing, vol. 1, pp. 123-126, Jan., 1992.
22. E. Dubois, "The sampling and reconstruction of time-varying imagery with application in video systems," Proc. IEEE, vol. 73, pp. 502-522, Apr. 1985.
23. M. I. Sezan, "An overview of convex projections theory and its applications to image recovery problems," Ultramicroscopy, no. 40, pp. 55-67, 1992.
24. H. J. Trussell and M. R. Civanlar, "Feasible solution in signal restoration," IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-32, pp. 201-212, 1984.
25. M. K. Ozkan, A. M. Tekalp, and M. I. Sezan, "POCS-based restoration of space-varying blurred images," IEEE Trans. Image Processing, vol. 3, pp. 450-454, Apr. 1994.