Abstract

We use the classification image technique to investigate the effect of white noise and various correlated Gaussian noise textures (low-pass, high-pass, and band-pass) on observer performance in detection and discrimination tasks. For these tasks, performance is generally enhanced by an observer’s ability to “prewhiten” correlated noise as part of the formation of a decision variable. We find that observer efficiency in these tasks is well represented by the measured classification images and that human observers show strong evidence of adaptation to different correlated noise textures. This adaptation is captured in the frequency weighting of the classification images.

© 2007 Optical Society of America

Visual signal detectability with two noise components: anomalous masking effects

Arthur E. Burgess, Xing Li, and Craig K. Abbey
J. Opt. Soc. Am. A 14(9) 2420-2442 (1997)

Effect of noise correlation on detectability of disk signals in medical imaging

K. J. Myers, H. H. Barrett, M. C. Borgstrom, D. D. Patton, and G. W. Seeley
J. Opt. Soc. Am. A 2(10) 1752-1759 (1985)

Pattern recognition in correlated and uncorrelated noise

Brianna Conrey and Jason M. Gold
J. Opt. Soc. Am. A 26(11) B94-B109 (2009)

Visual signal detection with two-component noise: low-pass spectrum effects

Arthur E. Burgess
J. Opt. Soc. Am. A 16(3) 694-704 (1999)

Frequency tuning of perceptual templates changes with noise magnitude

Craig K. Abbey and Miguel P. Eckstein
J. Opt. Soc. Am. A 26(11) B72-B83 (2009)