Abstract

This study examined how correlated, or filtered, noise affected efficiency for recognizing two types of signal patterns, Gabor patches and three-dimensional objects. In general, compared with the ideal observer, human observers were most efficient at performing tasks in low-pass noise, followed by white noise; they were least efficient in high-pass noise. Simulations demonstrated that contrast-dependent internal noise was likely to have limited human performance in the high-pass conditions for both signal types. Classification images showed that observers were likely adopting different strategies in the presence of low-pass versus white noise. However, efficiencies were underpredicted by the linear classification images and asymmetries were present in the classification subimages, indicating the influence of nonlinear processes. Response consistency analyses indicated that lower contrast-dependent internal noise contributed somewhat to higher efficiencies in low-pass noise for Gabor patches but not objects. Taken together, the results of these experiments suggest a complex interaction among signals, external noise spectra, and internal noise in determining efficiency in correlated and uncorrelated noise.

© 2009 Optical Society of America

Full Article  |  PDF Article

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (11)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (13)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription