Efficiency of the human observer for detecting a Gaussian signal at a known location in non-Gaussian distributed lumpy backgrounds.
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.
Park
Subok
S
National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD 20892, USA. subok.park@fda.hhs.gov
Gallas
Bradon D
BD
Badano
Aldo
A
Petrick
Nicholas A
NA
Myers
Kyle J
KJ
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D016011:Normal Distribution; D010363:Pattern Recognition, Automated / Q000379:methods*; D010364:Pattern Recognition, Visual / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013647:Task Performance and Analysis