Projection-based image restoration

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

Volumn 9, Issue 11, 1992, Pages 1914-1919

  Stark, Henry ^a   Olsen, Elwood T ^a  

^a ILLINOIS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0003610814     PISSN: 10847529     EISSN: 15208532     Source Type: Journal    
DOI: 10.1364/JOSAA.9.001914     Document Type: Article

References (14)

1. T. G. Stockham Jr., “Image processing in the context of a visual model,” Proc. IEEE 60, 828-842 (1972).
2. E. Oja and H. Ogawa, “Parametric projection filter for image and signal restoration,” IEEE Trans. Acoust. Speech Signal Process. ASSP-34, 1643-1653 (1986).
3. H. Ogawa, “Projection filter, Wiener filter, and Kurhumen- Loeve subspaces in digital image restoration,” J. Math. Anal. Appl. 114, 37-51 (1986).
4. D. C. Youla and H. Webb, “Image restoration by the method of convex projections: Part 1-Theory,” IEEE Trans. Med. Imaging MI-1, 81-94 (1982).
5. P. Kitagawa and W. Gersh, “A smoothness priors time- varying AR coefficient modeling of unstationary covariance time series,” IEEE Trans. Autom. Control AC-30, 48-56 (1985).
6. S.-J. Yeh, “Projection method applications to problems in neural nets and image recovery,” Ph.D. dissertation (Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, N.Y., 1991).
7. Q. J. Trussed and M. R. Civanlar, “The feasible solutions in signal restoration,” IEEE Trans. Acoust. Speech Signal Process. ASSP-32, 201-212 (1984).
8. H. Stark, ed., Image Recovery: Theory and Applications (Academic, Orlando, Fla., 1987).
9. I. Peng and H. Stark, “Signal recovery with similarity constraints,” J. Opt. Soc. Am. A 6, 844-851 (1989).
10. J. M. Sezan and J. H. Trussed, “Prototype image constraints for set-theoric image restorations,” IEEE Trans. Signal Process. SP-39, 2275-2285 (1991).
11. D. Yang, “Noise smoothing in direct Fourier position emission tomography,” M.S. thesis (Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, 111., 1991).
12. D. T. Kuan, A. A. Sawchuk, T. C. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal- dependent noise,” IEEE Trans. Pattern Anal. Mach. Int. PAMI-7, 165-177 (1985).
13. 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).
14. M. N. Wernick and C. T. Chen, “Superresolved tomography by convex projections and detector motion,” J. Opt. Soc. Am. A 9, 1547-1553 (1992).