Effects of 'local' clutter on human target detection

Spatial Vision

Volumn 19, Issue 1, 2006, Pages 37-60

  Ewing, Gary J ^a,c   Woodruff, Christopher J ^a   Vickers, Douglas ^b  

^a DEFENCE SCIENCE AND TECHNOLOGY ORGANISATION   (Australia)

^b UNIVERSITY OF ADELAIDE   (Australia)

^c Building 205 Laboratories   (Australia)

Author keywords

Clutter metric; Visual clutter simulation; Visual detection

Indexed keywords

CLUTTER METRIC; VISUAL CLUTTER SIMULATION; VISUAL DETECTION;

HUMAN ENGINEERING; PROBABILITY;

CLUTTER (INFORMATION THEORY);

ADULT; ARTICLE; COMPARATIVE STUDY; HUMAN; MIDDLE AGED; PATTERN RECOGNITION; PHOTOSTIMULATION; PHYSIOLOGY; PILOT STUDY; TASK PERFORMANCE;

ADULT; HUMANS; MIDDLE AGED; PATTERN RECOGNITION, VISUAL; PHOTIC STIMULATION; PILOT PROJECTS; TASK PERFORMANCE AND ANALYSIS;

EID: 30344435905     PISSN: 01691015     EISSN: None     Source Type: Journal    
DOI: 10.1163/156856806775009232     Document Type: Review

References (34)

1. Aviram, G. and Rotman, S. (2000a). Evaluating human detection performance of targets and false alarms, using a statistical texture image metric, Optical Engineering 39, 2285-2295.
2. Aviram, G. and Rotman, S. (2000b). Evaluation of human detection performance of targets embedded in natural and enhanced infrared images using image metrics, Optical Engineering 39, 885-896.
3. Barlow, H. (1958). Temporal and spatial summation in human vision at different background intensities, J. Physiol. 141, 337-350.
4. Bertilone, D. C., Caprari, R. S., Angeli, S. and Newsam, G. N. (1997). Spatial statistics of natural terrain imagery, i. non-Gaussian ir backgrounds and long-range correlation, Applied Optics 36, 9167-9176.
5. Bertilone, D. C., Caprari, R. S., Chapple, P. B. and Angeli, S. (1998). Spatial statistics of natural terrain imagery, ii. oblique visible backgrounds and stochastic simulatio, Optical Communication 150, 71-76.
6. Blackwell, R. H. (1946). Contrast thresholds of the human eye, J. Opt. Soc. Amer. 36, 624-643.
7. Burr, D. C., Morrone, M. C. and Ross, J. (1986). Local and global visual processing, Vision Research 26, 749-757.
8. Caelli, T. and Julesz, B. (1979). Psychophysical evidence for global processing in visual texture discrimination, J. Opt. Soc. Amer. 69, 675-678.
9. Chapple, P. (1997). Personal Communication.
10. Chen, L. and Tokuda, N. (2003). Robustness of regional matching scheme over global matching scheme, Artificial Intelligence 144, 213-232.
11. Doll, T. J., McWhorter, S. W. and Schmeider, D. E. (1993). Target and background characterization based on a simulation of human perception, in: Proceedings of the SPIE on Characterization, Propagation and Simulation of Sources and Backgrounds III, Vol. 1967, Watkins, W. R. (Ed.), pp. 432-454.
12. Ewing, G. J. and Woodruff, C. J. (1996). Comparison of jpeg and fractal based image compression on target acquisition by human observers, Optical Engineering 35, 284-288.
13. Gonzalez, R. and Wintz, P. (1987). In: Digital Image Processing, Chapter 7, pp. 336-340. Addison-Wiley.
14. Green, D. M. and Swets, J. A. (1966). Signal Detection Theory and Psychophysics. Penninsula Publishing, Los Altos, California, USA.
15. Hood, D. C. and Finkelstein, M. A. (1986). Sensitivity to light, in: Handbook of Perception and Human Performance, Vol. 1, 1st edn, Boff, L. K. and Thomas, J. (Eds.). John Wiley, New York.
16. Karbowiak, A. (1969a). In: Theory of Communication. Oliver and Boyd, Edinburgh.
17. Karbowiak, A. (1969b). In: Theory of Communication, p. 44. Oliver and Boyd, Edinburgh.
18. Keppel, G. (1991). In: Design and Analysis: A Researcher's Handbook, Chapter 7, Analysis of trend. Prentice Hall.
19. Knill, D. C., Field, D. and Kersten, D. (1990). Human discrimination of fractal images, J. Opt. Soc. Amer. A 7, 1113-1123.
20. Laming, D. (1986). Sensory Analysis. Academic Press.
21. Newsam, G. and Woodruff, C. (1991). Fractal random fields and their use in vision experiments, in: DICTA-91 Digital Image Computing: Techniques and Applications, pp. 365-372. Australian Pattern Recognition Society.
22. Overington, I. (1976a). In: Vision and Aquisition, Chapter 8, Rudimentary search modelling, pp. 164-174. Pentech Press, London.
23. Overington, I. (1976b). In: Vision and Aquisition, Chapter 4, Basic thresholds for detection, page 54. Pentech Press, London.
24. Overington, I. (1976c). In: Vision and Aquisition, Chapter 13, Background Structure, p. 236. Pentech Press, London.
25. Overington, I. (1982). Towards a complete model of photopic visual threshold, Optical Engineering 21, 2-13.
26. Pentland, A. P. (1984). Fractal-based image description of natural scenes, IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-6, 661-673.
27. Rotman, S., Tidhar, G. and Kowalczyk, M. (1994). Clutter metrics for target detection systems, IEEE Transactions on Aerospace and Electronic Systems 30, 81-90.
28. Thibos, L. (1989). Image processing by the human eye, in: Proceedings of SPIE on Visual Communications and Image Processing IV, Vol. 1199, Pearlman, W. A. (Ed.), pp. 1148-1153.
29. van der Schaaf, A. and van Hateran, J. (1996). Modelling the power spectra of natural images: Statistics and information, Vision Research 36, 2759-2770.
30. Wickens, T. D. (2001). Elementary Signal Detection Theory. Oxford University Press.
31. Wilson, H. R. (1995). Quantitative models for pattern detection and discrimination, in: Vision Models for Target Detection and Recognition, Peli, E. (Ed.), pp. 3-15. World Scientific.
32. Witus, and Ellis, (2003). Computational modeling of foveal target detection, Human Factors 45, 47-60.
33. Woodruff, C. J. and Newsam, G. N. (1994). Displaying undersampled imagery, Optical Engineering 33, 579-585.
34. Yaglom, A. (1987). Correlation Theory of Stationary and Related Random Functions, Springer Series in Statistics. Springer-Verlag, New York.