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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: James C. Wyant
  • Vol. 45, Iss. 21 — Jul. 20, 2006
  • pp: 5073–5085

Superresolution image reconstruction from a sequence of aliased imagery

S. Susan Young and Ronald G. Driggers  »View Author Affiliations


Applied Optics, Vol. 45, Issue 21, pp. 5073-5085 (2006)
http://dx.doi.org/10.1364/AO.45.005073


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Abstract

We present a superresolution image reconstruction from a sequence of aliased imagery. The subpixel shifts (displacement) among the images are unknown due to the uncontrolled natural jitter of the imager. A correlation method is utilized to estimate subpixel shifts between each low-resolution aliased image with respect to a reference image. An error-energy reduction algorithm is derived to reconstruct the high-resolution alias-free output image. The main feature of this proposed error-energy reduction algorithm is that we treat the spatial samples from low-resolution images that possess unknown and irregular (uncontrolled) subpixel shifts as a set of constraints to populate an oversampled (sampled above the desired output bandwidth) processing array. The estimated subpixel locations of these samples and their values constitute a spatial domain constraint. Furthermore, the bandwidth of the alias-free image (or the sensor imposed bandwidth) is the criterion used as a spatial frequency domain constraint on the oversampled processing array. The results of testing the proposed algorithm on the simulated low- resolution forward-looking infrared (FLIR) images, real-world FLIR images, and visible images are provided. A comparison of the proposed algorithm with a standard interpolation algorithm for processing the simulated low-resolution FLIR images is also provided.

© 2006 Optical Society of America

OCIS Codes
(100.2960) Image processing : Image analysis
(100.3190) Image processing : Inverse problems
(100.6640) Image processing : Superresolution

ToC Category:
Image Processing

History
Original Manuscript: November 1, 2005
Manuscript Accepted: December 29, 2005

Citation
S. Susan Young and Ronald G. Driggers, "Superresolution image reconstruction from a sequence of aliased imagery," Appl. Opt. 45, 5073-5085 (2006)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-45-21-5073


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References

  1. S. C. Park, M. K. Park, and M. G. Kang, "Superresolution image reconstruction: a technical overview," IEEE Signal Process. Mag. 20(3), 21-36 (2003). [CrossRef]
  2. J. M. Schuler and D. A. Scribner, "Dynamic sampling, resolution enhancement, and superresolution," in Analysis of Sampled Imaging Systems, R. H. Vollmerhausen and R. G. Driggers, eds. (SPIE Press , 2000), pp. 125-138.
  3. S. Borman and R. L. Stevenson, "Superresolution from image sequences--a review," Proc. 1998 Midwest Symp. Circuits and Systems (IEEE, 1998), pp. 374-378.
  4. M. Bertero and C. Demol, "Superresolution by data inversion," Progress In Optics, Vol. 36 (Elsevier North-Holland, 1996), pp. 129-178.
  5. Z. Zalevsky, N. Shamir, and D. Mendlovic, "Geometrical superresolution in infrared sensor: experimental verification," Opt. Eng. 43, 1401-1406 (2004). [CrossRef]
  6. M. Ben-Ezra, A. Zomet, and S. K. Nayar, "Video superresolution using controlled subpixel detector shifts," IEEE Trans. Pattern Anal. Mach. Intell. 27, 977-987 (2005). [CrossRef]
  7. B. K. P. Horn and B. G. Schunk, "Determining optical flow," Artif. Intell. 17, 185-203 (1981). [CrossRef]
  8. D. J. Heeger, "Model for the extraction of image flow," J. Opt. Soc. Am. A 4, 1455-1471 (1987).
  9. J. R. Bergen, P. J. Burt, K. Hanna, R. Hingorari, P. Jeanne, and S. Peleg, "Dynamic multiple-motion computation, inArtificial Intelligence and Computer Vision: Proceedings of the Israeli Conference, Y. A. Feldman and A. Bruckstein, eds. (Elsevier, 1991), pp. 147-156.
  10. M. Bierling, "Displacement estimation by hierarchical blockmatching," in Visual Communications and Image Processing '88,Proc. SPIE 1001, 942-951 (1988).
  11. R. P. Kleihorst, R. L. Lagendijk, and J. Biemond, "Noise reduction of image sequences using motion compensation and signal decomposition," IEEE Trans. Image Processing 4, 274-284 (1985). [CrossRef]
  12. H. S. Stone, M. T. Orchard, E.-C. Chang, and S. A. Martucci, "A fast direct Fourier-based algorithm for subpixel registration of images," IEEE Trans. Geosci. Remote Sens. 39, 2235-2243 (2001). [CrossRef]
  13. S. P. Kim and W. Y. Su, "Subpixel accuracy image registration by spectrum cancellation," Proceedings of ICASSP-93--1993 IEEE International Conference on Acoustics, Speech, and Signal Processing (1993), Vol. 5, pp. 153-156.
  14. C. L. L. Hendriks and L. J. van Vliet, "Improving resolution to reduce aliasing in an undersampled image sequence," in Sensors and Camera Systems for Scientific, Industrial, and Digital Photography Applications,Proc. SPIE 3965, 214-222 (2000). [CrossRef]
  15. H. Foroosh, J. B. Zerubia, and M. Berthod, "Extension of phase correlation to subpixel registration," IEEE Trans. Image Process. 11, 188-200 (2002). [CrossRef]
  16. A. J. Patti, M. I. Sezan, and A. M. Tekalp, "Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time," IEEE Trans. Image Process. 6, 1064-1076 (1997). [CrossRef]
  17. N. K. Bose, "Superresolution from image sequence," Proceedings of IEEE International Conference on Image Processing 2004 (IEEE, 2004), pp. 81-86.
  18. D. T. Sandwell, "Biharmonic spline interpolation of Geo-3 and Seasat altimeter data," Geophys. Res. Lett. 14, 139-142 (1987).
  19. S. Lertrattanapanich and N. K. Bose, "High resolution image formation from low resolution frams using Delaunay Triangulation," IEEE Trans. Image Process. 11, 1427-1441 (2002). [CrossRef]
  20. H. Ur and D. Gross, "Improved resolution from subpixel shifted pictures," CVGIP: Graph. Models Image Process. 54, 181-186 (1992). [CrossRef]
  21. M. C. Chiang and T. E. Boult, "Efficient superresolution via image warping," Image Vis. Comput. 18, 761-771 (2000). [CrossRef]
  22. R. A. Gonsalves and F. Khaghani, "Superresolution based on low-resolution, warped images," in Applications of Digital Image Processing XXV,Proc. SPIE 4790, 11-20 (2002). [CrossRef]
  23. M. S. Alam, J. G. Bognar, R. C. Hardie, and B. J. Yasuda, "Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames," IEEE Trans. Instrum. Meas. 49, 915-923 (2000). [CrossRef]
  24. F. M. Candocia and J. C. Principe, "Superresolution of images based on local correlations," IEEE Trans. Neural Netw. 10, 372-380 (1999). [CrossRef]
  25. M. Irani and S. Peleg, "Image sequence enhancement using multiple motions analysis," Proceedings of 1992 IEEE Computer Society Conference on Computer Vision and Pattern Analysis (IEEE, 1992), pp. 216-221.
  26. R. Y. Tsai and T. S. Huang, "Multiple frame image restoration and registration," in Advances in Computer Vision and Image Processing (JAI Press Inc., 1984), pp. 317-339.
  27. J. Mateos, M. Vega, R. Molina, and A. K. Katsaggelos, "Baysian image estimation from an incomplete set of blurred, undersampled low resolution images," Proceedings Lecture Notes in Computer Science 2652, Pattern Recognition and Image Analysis (IEEE, 2003), pp. 538-546.
  28. R. R. Schulz and R. L. Stevenson, "Extraction of high-resolution frames from video sequences," IEEE Trans. Image Process. 5, 996-1011 (1996). [CrossRef]
  29. R. C. Hardie, K. J. Barnard, and E. E. Armstrong, "Joint MAP registration and high-resolution image estimation using a sequence of undersampled images," IEEE Trans. Image Process. 6, 1621-1633 (1997). [CrossRef]
  30. M. Elad and Y. Hel-Or, "A fast superresolution reconstruction algorithm for pure translational motion and common space-invariant blur," IEEE Trans. Image Process. 10, 1187-1193 (2001). [CrossRef]
  31. D. Rajan and S. Chaudhuri, "Simultaneous estimation of superresolved scene and depth map from low resolution defocused observations," IEEE Trans. Pattern Anal. Mach. Intell. 25, 1102-1115 (2003). [CrossRef]
  32. S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, "Fast and robust multiframe superresolution," IEEE Trans. Image Process. 13, 1327-1344 (2004). [CrossRef]
  33. E. S. Lee and M. G. Kang, "Regularized adaptive high-resolution image reconstruction considering inaccurate subpixel registration," IEEE Trans. Image Process. 12, 826-837 (2003). [CrossRef]
  34. A. Papoulis, "A new algorithm in spectral analysis and band-limited extrapolation," IEEE Trans. on Circuits Syst. 22, 735-742 (1975). [CrossRef]
  35. R. W. Gerchberg, "Superresolution through error energy reduction," Opt. Acta 21, 709-720 (1974).
  36. P. De Santis and F. Gori, "On an iterative method for superresolution," Opt. Acta 22, 691-695 (1975).
  37. H. Stark and P. Oskoui, "High-resolution image recovery from image-plane arrays, using convex projections," J. Opt. Soc. Am. A 6, 1715-1726 (1989).
  38. K. Krapels, R. G. Driggers, S. Murrill, J. Schuler, M. Thielke, and S. S. Young, "Superresolution performance for undersampled imagers," in Defense and Security Symposium (Formerly AeroSense),Proc. SPIE 5407, 139-149 (2004). [CrossRef]
  39. P. Vandewalle, S. Susstrunk, and M. Vetterli, "Superresolution images reconstruction from aliased images," in Visual Communications and Image Processing,Proc. SPIE 5150, 1398-1405 (2003). [CrossRef]
  40. P. Vandewalle, L. Sbaiz, J. Vandewalle, and M. Vetterli, "How to take advantage of aliasing in bandlimited signals," Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2004), pp. 948-951.
  41. S. S. Young, "Alias-free image subsampling using Fourier-based windowing methods," Opt. Eng. 43, 843-855 (2004). [CrossRef]
  42. http://www.cns.nvu.edu/∼david/ftp/registration/.
  43. J. M. Schuler, J. G. Howard, P. Warren, and D. Scribner, "TARID-based image superresolution," in Infrared and Passive Millimeter-Wave Imaging Systems; Design, Analysis, Modeling, and Testing, Proc SPIE 4719, 247-254 (2002). [CrossRef]

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