Methods to detect objects in photon-limited images

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

Volumn 23, Issue 2, 2006, Pages 272-278

  Abu Naser, Ahmad ^a   Galatsanos, Nikolas P ^b   Wernick, Miles N ^a  

^a Illinois Institute of Technology   (United States)

^b UNIVERSITY OF IOANNINA   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; IMAGE QUALITY; IMAGE RECONSTRUCTION; MAXIMUM LIKELIHOOD ESTIMATION; PHOTODEGRADATION; PHOTONS; SIGNAL DETECTION;

DELTA FUNCTION; GENERALIZED LIKELIHOOD RATIO TEST (GLRT); IMAGE DEGRADATION; IMPULSE RESTORATION (IR); PHOTON-LIMITED IMAGE; POISSON NOISE;

OBJECT RECOGNITION;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; METHODOLOGY; PHOTON; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL;

ALGORITHMS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; PHOTONS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 33644537644     PISSN: 10847529     EISSN: None     Source Type: Journal    
DOI: 10.1364/JOSAA.23.000272     Document Type: Article

References (24)

1. S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory (Prentice Hall, 1998).
2. A. K. Jain, Fundamentals of Digital Image Processing (Prentice Hall, 1989).
3. G. M. Morris, "Scene matching using photon-limited images," J. Opt. Soc. Am. A 1, 482-488 (1984).
4. M. N. Wernick and G. M. Morris, "Image classification at low light levels," J. Opt. Soc. Am. A 3, 2179-2187 (1986).
5. R. E. Sequira, J. Gubner, and B. E. A. Saleh, "Image detection under low-level illumination," IEEE Trans. Image Process. 2, 18-26 (1993).
6. M. N. Wernick and J. N. Aarsvold, eds., Emission Tomography: The Fundamentals of PET and SPECT (Academic, 2004).
7. J. Ben-Arie and K. Rao, "A novel approach to template matching by non-orthogonal image expansion," IEEE Trans. Circuits Syst. Video Technol. 3, 71-84 (1993).
8. J. Ben-Arie and K. Rao, "Optimal template matching by non-orthogonal image expansion using restoration," Mach. Vision Appl. 7, 69-81 (1994).
9. C. Chatwin, R. Wang, and R. Young, "Assessment of a Wiener filter synthetic discriminant function for optical correlation," Opt. Lasers Eng. 22, 33-51 (1995).
10. E. Marom and H. Inbar, "New interpretations of Wiener filters for image recognition," J. Opt. Soc. Am. A 13, 1325-1330 (1996).
11. B. Javidi, F. Parchekani, and G. Zhang, "Minimum-mean-square error filters for detecting a noisy target in background noise," Appl. Opt. 35, 6964-6975 (1996).
12. R. Dufour, E. Miller, and N. P. Galatsanos, "Geometric parameter estimation with a multiscale template library," in Automatic Target Recognition X, F. A. Sadjadi, ed., Proc. SPIE 4050, 397-407 (2000).
13. R. Dufour, E. Miller, and N. P. Galatsanos, "Template matching based object recognition with unknown geometry," IEEE Trans. Image Process. 11, 1385-1396 (2002).
14. A. Abu-Naser, "Object recognition based on impulse restoration for images in Gaussian noise," M.S. thesis (Illinois Institute of Technology, 1996).
15. A. Abu-Naser, N. P. Galatsanos, M. N. Wernick, and D. Schonfeld, "Object recognition based on impulse restoration with use of the expectation maximization algorithm," J. Opt. Soc. Am. A 15, 2327-2339 (1998).
16. A. Abu-Naser, N. P. Galatsanos, and M. N. Wernick, "ML and Bayesian impulse restoration based object recognition in photon limited noise," in Proceedings of the 2002 IEEE International Conference on Image Processing (IEEE Press, 2002), Vol. 2, pp. 837-840.
17. A. Dempster, N. Laird, and D. Rubin, "Maximum-likelihood from incomplete data," J. R. Stat. Soc. Ser. B. Methodol. 39, 1-38 (1977).
18. L. Shepp and Y. Vardi, "Maximum likelihood reconstruction for emission tomography," IEEE Trans. Med. Imaging 1, 113-122 (1982).
19. K. Lange and R. Carson, "EM reconstruction algorithms for emission and transmission tomography," J. Comput. Assist. Tomogr. 8, 306-316 (1984).
20. D. S. Lalush and M. N. Wernick, "Iterative image reconstruction," in Ref. 6, pp. 443-472.
21. S. Geman and D. Geman, "Stochastic distributions, and the Bayesian restoration of images," IEEE Trans. Pattern Anal. Mach. Intell. 6, 721-741 (1984).
22. P. J. Green, "Bayesian reconstructions from emission tomography data using a modified EM algorithm," IEEE Trans. Med. Imaging 9, 84-93 (1990).
23. R. Swensson, "Unified measurement of observer performance and localizing target objects on images," Med. Phys. 23, 1709-1725 (1996).
24. B. E. A. Saleh and M. C. Teich, Fundamentals of Photonics (Wiley, 1991).