OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Vol. 15, Iss. 4 — Apr. 1, 1998
  • pp: 791–801

Fusion of images on affine sampling grids

Douglas Granrath and James Lersch  »View Author Affiliations


JOSA A, Vol. 15, Issue 4, pp. 791-801 (1998)
http://dx.doi.org/10.1364/JOSAA.15.000791


View Full Text Article

Enhanced HTML    Acrobat PDF (1001 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

We present a method for combining multiple images of a common object assuming two-dimensional (2D) affine transformations between the image sampling grids. Our method is based upon the projection-onto-convex-sets approach of YehStark [J. Opt. Soc. Am. A 7, 491 (1990)]. Each image frame constitutes a single projection in our approach. We derive a frame projection algorithm under the 2D affine transform assumption that uses one-dimensional fast Fourier transform operations. We demonstrate that all the parameters required for successful image fusion can be estimated with sufficient accuracy from the image data proper. Four 64×64-pixel images taken by the Galileo Orbiter spacecraft of the asteroid Gaspra were fused to produce a result with twice the sampling rate and significantly improved spatial resolution. The total processing time was 55 s on a single-processor workstation.

© 1998 Optical Society of America

OCIS Codes
(100.3020) Image processing : Image reconstruction-restoration

History
Original Manuscript: May 22, 1997
Revised Manuscript: October 13, 1997
Manuscript Accepted: October 27, 1997
Published: April 1, 1998

Citation
Douglas Granrath and James Lersch, "Fusion of images on affine sampling grids," J. Opt. Soc. Am. A 15, 791-801 (1998)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-15-4-791


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. A. Papoulis, Signal Analysis (McGraw-Hill, New York, 1977), pp. 193–196.
  2. R. Tsai, T. Huang, “Multiframe image restoration and registration,” in Advances in Computer Vision and Image Processing (JAI Press, London, 1984), Vol. 1, pp. 317–339.
  3. S. P. Kim, N. K. Bose, H. M. Valenzuela, “Recursive reconstruction of high resolution image from noisy undersampled multiframes,” IEEE Trans. Acoust. Speech Signal Process. 38, 1013–1027 (1990). [CrossRef]
  4. G. Jacquemod, “Image resolution enhancement using subpixel camera displacement,” Signal Process. 26, 39–146 (1992). [CrossRef]
  5. A. M. Tekalp, M. K. Ozkan, M. I. Sezan, “High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration,” in Proceedings of the IEEE Conference on Acoustics, Speech, and Signal Processing (Institute of Electrical and Electronics Engineers, New York, 1990), Vol. III, 169–172.
  6. K. D. Sauer, J. P. Allebach, “Iterative reconstruction of band-limited images from nonuniformly spaced samples,” IEEE Trans. Circuits Syst. CAS-34, 1497–1506 (1987). [CrossRef]
  7. A. J. Patti, M. I. Sezan, A. M. Tekalp, “High-resolution image reconstruction from a low-resolution image sequence in the presence of time-varying motion blur,” presented at the International Conference on Image Processing, Austin, Texas, November 1994.
  8. S. Yeh, H. Stark, “Iterative and one-step reconstruction from nonuniform samples by convex projections,” J. Opt. Soc. Am. A 7, 491–499 (1990). [CrossRef]
  9. P. Cheeseman, R. Kanefsky, R. Kraft, J. Stutz, R. Hanson, “Super-resolved surface reconstruction from multiple images,” (NASA, Washington, D.C., 1994).
  10. J. L. Yen, “On nonuniform sampling of bandwidth-limited signals,” IRE Trans. Circuit Theory CT-3; 251–257; (1956). [CrossRef]
  11. D. S. Chen, J. P. Allebach, “Analysis of error in reconstruction of two-dimensional signals from irregularly spaced samples,” IEEE Trans. Acoust. Speech Signal Process. ASSP-35, 173–180 (1987). [CrossRef]
  12. L. G. Gubin, B. T. Polyak, E. V. Raik, “The method of projections for finding the common point of convex sets,” USSR Comput. Math. Math. Phys. 7, 1–24 (1967). [CrossRef]
  13. D. H. Bailey, P. N. Swarztrauber, “The fractional Fourier transform and applications,” SIAM (Soc. Ind. Appl. Math.) Rev. 33, 389–404 (1991).
  14. L. I. Bluestein, “A linear filtering approach to the computation of the discrete Fourier transform,” IEEE Trans. Audio Electroacoust. AE-18, 451–455 (1970). [CrossRef]
  15. D. I. Barnea, H. F. Silverman, “A class of algorithms for fast digital image registration,” IEEE Trans. Comput. IEEE Trans. Comput. C-21, 179–186 (1972). [CrossRef]
  16. W. K. Pratt, “Correlation techniques of image registration,” IEEE Trans. Aerosp. Electron. Syst. AES-10, 353–357 (1974). [CrossRef]
  17. E. DeCastro, C. Morandi, “Registration of translated and rotated images using finite Fourier transforms,” IEEE Trans. Pattern. Anal. Mach. Intell. PAMI-9, 700–703 (1987). [CrossRef]
  18. M. Irani, S. Peleg, “Improving resolution by image registration,” CVGIP: Graphic. Models Image Process. 53, 231–239 (1991).
  19. B. S. Reddy, B. N. Chatterji, “An FFT-based technique for translation, rotation, and scale-invariant image registration,” IEEE Trans. Image Process. 5, 1266–1271 (1996). [CrossRef] [PubMed]
  20. A. V. Oppenheim, R. W. Schafer, Digital Signal Processing (Prentice-Hall, Englewood Cliffs, N.J., 1975), pp. 487–490.

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

Figures

Fig. 1 Fig. 2 Fig. 3
 
Fig. 4 Fig. 5
 

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited