Abstract

A previous study [J. Opt. Soc. Am. A 22, 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. A 16, 694 (1999) and J. Opt. Soc. Am. A 18, 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.

© 2007 Optical Society of America

Channelized-ideal observer using Laguerre-Gauss channels in detection tasks involving non-Gaussian distributed lumpy backgrounds and a Gaussian signal

Subok Park, Harrison H. Barrett, Eric Clarkson, Matthew A. Kupinski, and Kyle J. Myers
J. Opt. Soc. Am. A 24(12) B136-B150 (2007)

Efficiency of the human observer detecting random signals in random backgrounds

Subok Park, Eric Clarkson, Matthew A. Kupinski, and Harrison H. Barrett
J. Opt. Soc. Am. A 22(1) 3-16 (2005)

Effect of random background inhomogeneity on observer detection performance

J. P. Rolland and H. H. Barrett
J. Opt. Soc. Am. A 9(5) 649-658 (1992)

Channelized Hotelling observers for the assessment of volumetric imaging data sets

Ljiljana Platiša, Bart Goossens, Ewout Vansteenkiste, Subok Park, Brandon D. Gallas, Aldo Badano, and Wilfried Philips
J. Opt. Soc. Am. A 28(6) 1145-1163 (2011)

Efficient estimation of ideal-observer performance in classification tasks involving high-dimensional complex backgrounds

Subok Park and Eric Clarkson
J. Opt. Soc. Am. A 26(11) B59-B71 (2009)