Classification image weights and internal noise level estimation

Journal of Vision

Volumn 2, Issue 1, 2002, Pages 121-131

  Ahumada Jr , Albert J ^a  

^a NASA AMES RESEARCH CENTER   (United States)

Author keywords

Detection; Discrimination; Noise; Vision

Indexed keywords

ARTICLE; CLASSIFICATION; CONTROLLED STUDY; HUMAN; HYPOTHESIS; IMAGE ANALYSIS; IMAGE QUALITY; MATHEMATICAL COMPUTING; NOISE MEASUREMENT; NORMAL DISTRIBUTION; NORMAL HUMAN; PSYCHOPHYSIOLOGY; SIGNAL DETECTION; SIGNAL NOISE RATIO; STIMULUS RESPONSE; VISUAL DISCRIMINATION; ALGORITHM; COMPUTER SIMULATION; DISCRIMINANT ANALYSIS; PATTERN RECOGNITION; PERCEPTIVE DISCRIMINATION; PHYSIOLOGY; PSYCHOLOGICAL MODEL;

ALGORITHMS; COMPUTER SIMULATION; DISCRIMINANT ANALYSIS; HUMANS; MODELS, PSYCHOLOGICAL; PATTERN RECOGNITION, VISUAL; SIGNAL DETECTION (PSYCHOLOGY);

EID: 0036974726     PISSN: 15347362     EISSN: None     Source Type: Journal    
DOI: 10.1167/2.1.8     Document Type: Article

References (24)

1. Abbey, C. K., & Eckstein, M. P. (2000). Estimates of human-observer templates for simple detection tasks in correlated noise. Proceedings of SPIE, 3981, 70-77.
2. Abbey, C. K., & Eckstein, M. P. (2001a). Maximum-likelihood and maximum a-posteriori estimates of human-observer templates. Proceedings of SPIE, 4324, 114-122.
3. Abbey, C. K., & Eckstein, M. P. (2001b). Theory for estimating human-observer templates in two-alternative forced-choice experiments. In M. F. Insana & R. Leahy (Eds.), Proceedings of the 17th International Conference on Inferential Processes in Medical Imaging. Berlin: Springer-Verlag.
4. Abbey, C. K. & Eckstein, M. P. (2002). Classification image analysis: Estimation and statistical inference for two-alternative forced-choice experiments. Journal of Vision, 2(1), 66-78, http://journalofvision.org/2/1/5/, DOI 10.1167/2.1.5.
5. Abbey, C. K., Eckstein, M. P., & Bochud, F. O. (1999). Estimation of human-observer templates for 2 alternative forced choice tasks. Proceedings of SPIE, 3663, 284-295.
6. Ahumada, A. J., Jr. (1967). Detection of tones masked by noise: A comparison of human observers with digital-computer-simulated energy detectors of varying bandwidths. Unpublished doctoral dissertation, University of California, Los Angeles. Available as Technical Report No. 29, Human Communications Laboratory, Department of Psychology, University of California, Los Angeles.
7. Ahumada, A. J., Jr. (1996). Perceptual classification images from vernier acuity masked by noise [Abstract]. Perception, 26(Suppl. 1), 18.
8. Ahumada, A. J., Jr., & Beard, B. L. (1998). Response classification images in vernier acuity [Abstract]. Investigative Ophthalmology and Visual Science, 39(Suppl. 4), S1109.
9. Ahumada, A. J., Jr., & Beard, B. L. (1999). Classification images for detection [Abstract]. Investigative Ophthalmology and Visual Science, 40 (Suppl. 4), S572.
10. Ahumada, A. J., Jr., & Lovell, J. (1971). Stimulus features in signal detection. Journal of the Acoustical Society of America, 49, 1751-1756.
11. Ahumada, A. J., Jr., Marken, R., & Sandusky, A. (1975). Time and frequency analyses of auditory signal detection. Journal of the Acoustical Society of America, 57, 385-390.
12. Barth, E., Beard, B. L., & Ahumada, A. J., Jr. (1999). Nonlinear features in vernier acuity. Proceedings of SPIE, 3644, 88-96.
13. Beard, B. L., & Ahumada, A. J., Jr. (1997). Relevant image features for vernier acuity [Abstract]. Perception, 26, 38.
14. Beard, B. L., & Ahumada, A. J., Jr. (1998). Technique to extract relevant image features for visual tasks. Proceedings of SPIE, 3299, 79-85.
15. Beard, B. L., & Ahumada, A. J., Jr. (1999). Detection in fixed and random noise in foveal and parafoveal vision explained by template learning. Journal of the Optical Society of America A, 16, 755-763.
16. Beard, B. L., & Ahumada, A. J. (2000). Response classification images for parafoveal vernier acuity [Abstract]. Investigative Ophthalmology and Visual Science, 41(Suppl. 4), S804.
17. Burgess, A. E., & Colborne, B. (1988). Visual signal detection. IV. Observer inconsistency. Journal of the Optical Society of America A, 5, 617-628.
18. Findlay, J. M. (1973). Feature detectors and vernier acuity. Nature, 241, 135-137.
19. Foley, J. M. (1994). Human luminance pattern-vision mechanisms: Masking experiments require a new model. Journal of the Optical Society of America A, 11, 1710-1719.
20. Green, D. M., & Swets, J. A. (1966). Signal detection theory. New York: Wiley.
21. Murray, R. F., Bennett, P. J., & Sekuler, A. B. (2002). Optimal methods for calculating classification images: Weighted sums. Journal of Vision, 2 (1), 79-104, http://journalofvision.org/2/1/6/, DOI 10.1167/2.1.6
22. Richards, V. M., & Zhu, S. (1994). Relative estimates of combination weights, decision criteria, and internal noise based on correlation coefficients. Journal of the Acoustical Society of America, 95, 423-434.
23. Solomon, J. A. (2002). Noise reveals visual mechanisms of detection and discrimination. Journal of Vision, 2(1), 105-120, http://journalofvision.org/2/1/7/, DOI 10.1167/2.1.7.
24. Waugh, S. J., Levi, D. M., & Carney, T. (1993). Orientation, masking, and vernier acuity for line targets. Vision Research, 33, 1619-1638.