1. Efficiency of the human observer for detecting a Gaussian signal at a known location in non-Gaussian distributed lumpy backgrounds.
- Author
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Park S, Gallas BD, Badano A, Petrick NA, and Myers KJ
- Subjects
- Algorithms, Computer Simulation, Humans, Normal Distribution, Reproducibility of Results, Sensitivity and Specificity, Artificial Intelligence, Image Interpretation, Computer-Assisted methods, Models, Biological, Models, Statistical, Pattern Recognition, Automated methods, Pattern Recognition, Visual physiology, Task Performance and Analysis
- Abstract
A previous study [J. Opt. Soc. Am. A22, 3 (2005)] has shown that human efficiency for detecting a Gaussian signal at a known location in non-Gaussian distributed lumpy backgrounds is approximately 4%. This human efficiency is much less than the reported 40% efficiency that has been documented for Gaussian-distributed lumpy backgrounds [J. Opt. Soc. Am. A16, 694 (1999) and J. Opt. Soc. Am. A18, 473 (2001)]. We conducted a psychophysical study with a number of changes, specifically in display-device calibration and data scaling, from the design of the aforementioned study. Human efficiency relative to the ideal observer was found again to be approximately 5%. Our variance analysis indicates that neither scaling nor display made a statistically significant difference in human performance for the task. We conclude that the non-Gaussian distributed lumpy background is a major factor in our low human-efficiency results.
- Published
- 2007
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