Iterative Maximum Likelihood Displacement Field Estimation in Quantum-Limited Image Sequences

IEEE Transactions on Image Processing

Volumn 4, Issue 6, 1995, Pages 743-751

  Chan, Cheuk L ^a   Katsaggelos, Aggelos K ^a  

^a PAR Government Systems Corp   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE MAXIMUM LIKELIHOOD DISPLACEMENT FIELD ESTIMATION; PIXELS; QUANTUM LIMITED IMAGE SEQUENCES; STEREO MATCHING;

ALGORITHMS; IMAGE ANALYSIS; IMAGE QUALITY; ITERATIVE METHODS; PARAMETER ESTIMATION; REGRESSION ANALYSIS; SIGNAL DETECTION; STATISTICAL METHODS; TELECONFERENCING;

IMAGE PROCESSING;

EID: 0029322258     PISSN: 10577149     EISSN: 19410042     Source Type: Journal    
DOI: 10.1109/83.388077     Document Type: Article

References (39)

1. M. Bertero, T. A. Poggio, and V. Torre, “Ill-posed problems in early vision” Proc. IEEE, vol. 76, pp. 869-889, Aug. 1988.
2. A. Macovski, Medical Imaging Systems. Englewood Cliffs, NJ: Prentice Hall, 1983.
3. C. L. Chan, A. K. Katsaggelos, and A. V. Sahakian, “Image sequence filtering in quantum-limited noise with applications to low-dose fluoroscopy” IEEE Trans. Med. Imag., vol. 12, pp. 610-621, Sept. 1993.
4. R. E. Sequeira, J. A. Gubner, and B. E. A. Saleh, “Image detection under low-level illumination” IEEE Trans. Image Processing, vol. 2, pp. 18-26, Jan. 1993.
5. S. C. Pohlig, “An algorithm for detection of moving optical targets” IEEE Trans. Aerosp. Electron. Syst., vol. 25, pp. 56-63, Jan. 1989.
6. Y. Chen, “On suboptimal detection of 3-dimensional moving targets” IEEE Trans. Aerosp. Electron. Syst., vol. 25, pp. 343-350, May 1989.
7. M. S. Mort and M. D. Srinath, “Maximum-likelihood image registration with subpixel accuracy” Proc. SPIE, vol. 974, pp. 38-44, 1988.
8. N. M. Namazi and C. H. Lee, “Nonuniform image motion estimation from noisy data” IEEE Trans. Acoust., Speech, Signal Processing, vol. 38, pp. 364-366, Feb. 1990.
9. J. M. Anderson and G. B. Giannakis, “Noise insensitive image motion estimation using cumulants” in Proc. ICASSP, 1991, vol. 4, pp. 2721-2724.
10. J. C. Brailean and A. K. Katsaggelos, “A recursive nonstationary MAP displacement vector field estimation algorithm” Trans. Image Processing, vol. 4, pp. 416-429, Apr. 1995.
11. —, “Recursive displacement estimation and restoration of noisy-blurred image sequences” in Proc. ICASSP, 1993, vol. V, pp. 273-276.
12. J. Konrad and E. Dubois, “Bayesian estimation of motion vector fields” IEEE Trans. Pattern Anal. Machine Intell., vol. 14, pp. 910-927, Sept. 1992.
13. I. M. Abdelqader and S. A. Rajala, “Motion estimation from noisy image data” in Proc. ICASSP, 1993, vol. V, pp. 209-212.
14. G. M. Morris, “Scene matching images” J. Opt. Soc. Amer. A, vol. 1, pp. 482-488, May 1984.
15. A. O. Hero, “Lower bounds on estimator performance for energy-invariant parameters of multidimensional Poisson processes” IEEE Trans. Inform. Theory, vol. 35, pp. 843-858, July 1989.
16. —, “Timing estimation for a filtered Poisson process in Gaussian noise” IEEE Trans. Inform. Theory, vol. 37, pp. 92-106, Jan. 1991.
17. N. Antoniadis and A. O. Hero, “Time delay estimation for filtered Poisson processes using an EM-type algorithm” in Proc. ICASSP, 1992, vol. 5, pp. 289-292.
18. A. P. Dempster, N. Laird, and D. Rubin, “Maximum likelihood from incomplete data via the EM algorithm” J. Royal Statist. Soc. B, vol. 39, pp. 1-37, 1977.
19. B. J. Slocumb and D. L. Snyder, “Maximum likelihood estimation applied to quantum-limited optical position-sensing” Proc. SPIE, vol. 1304, pp. 165-176, 1990.
20. D. L. Snyder and M. I. Miller, Random Point Processes in Time and Space, 2nd ed. New York: Springer-Verlag, 1991.
21. D. L. Snyder and T. J. Schulz, “High-resolution imaging at low-light levels through weak turbulence” J. Opt. Soc. Amer. A, vol. 7, pp. 1251-1265, 1990.
22. T. J. Holmes, “Blind deconvolution of quantum-limited incoherent imagery: Maximum-likelihood approach” J. Opt. Soc. Amer. A, vol. 9, pp. 1052-1061, July 1992.
23. J. M. Mendel, Maximum-Likelihood Deconvolution: A Journey into Model-Based Signal Processing. New York: Springer-Verlag, 1990.
24. C. M. Lo and A. A. Sawchuk, “Nonlinear restoration of filtered images with Poisson noise” Proc. SPIE, vol. 207, pp. 84-95, 1979.
25. 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. Machine Intell., vol. 7, pp. 653-665, Mar. 1985.
26. S. S. Jiang and A. A. Sawchuk, “Noise updating repeated Wiener filter and other adaptive noise smoothing filters using local image statistics” Appl. Opt., vol. 25, pp. 2326-2337, July 1986.
27. T. Hebert and R. Leahy, “A generalized EM algorithm for 3-D Bayesian reconstruction from Poisson data using Gibbs priors” IEEE Trans. Med. Imag., vol. 8, pp. 194-202, June 1989.
28. C. L. Chan, A. K. Katsaggelos, and A. V. low-dosage cine-angiographic image sequences using a modified expectation maximization algorithm” Proc. SPIE, vol. 1818, pp. 290-298, Nov. 1992.
29. A. Papoulis, Probability, Random Variables, and Stochastic Processes, 2nd ed. New York: McGraw-Hill, 1984.
30. M. Segal, E. Weinstein, and B. R. Musicus, “Estimate-maximize algorithms for multichannel time delay and signal estimation” IEEE Trans. Signal Processing, vol. 39, pp. 1-16, Jan. 1991.
31. N. M. Namazi and J. A. Stuller, “A new approach to signal registration with emphasis to variable time delay estimation” IEEE Trans. Acoust., Speech, Signal Processing, vol. 35, pp. 1649-1660, Dec. 1987.
32. J. A. Stuller, “Maximum-likelihood estimation of time-varying I” IEEE Trans. on Acoust., Speech, Signal Proc., vol. ASSP-35, pp. 300-313, Mar. 1987.
33. A. N. Compression. New York, NY: Plenum, 1988.
34. P. S. Maybeck, Stochastic Models, Estimation, and Control, vol. 1. San Diego: Academic, 1979.
35. C. L. Chan, B. J. Sullivan, A. V. Sahakian, A. K. Katsaggelos, T. Frohlich, and E. Byrom, “Spatio-temporal filtering of digital angiographic image sequences corrupted by quantum mottle” Proc. SPIE, vol. 1450, pp. 208-217, 1991
36. J. Biemond, L. Looijenga, D. E. Boekee, and R. H. J. M. Plompen, “A pel-recursive Wiener-based displacement algorithm” Signal Proc., vol. 13, pp. 399-412, 1987.
37. S. N. Efstratiadis and A. K. Katsaggelos, “Nonstationary AR modeling and constrained recursive estimation of the displacement field” IEEE Trans. Circuits Syst. [Video Technol.], vol. 2, pp. 334-346, Dec. 1992.
38. C. L. Chan, J. C. Brailean, A. K. Katsaggelos, and A. V. Sahakian, “Maximum a posteriori displacement field estimation in quantum-limited image sequences” Proc. SPIE, Nov. 1993, vol. 2094, pp. 396-407.
39. C. noise smoothing filters for quantum-limited images” to appear in IEEE Trans. Image Processing, Sept. 1995.