Paper
4 May 2004 Observer models and human visual detection performance with different targets
Author Affiliations +
Abstract
Prior publications have shown that ideal observer models provide a good estimate of measured d' values for varying noise amplitude and target strength after allowing for observer internal noise and human efficiency. To provide a consistent estimate of visual performance in general applications, the internal noise and human efficiency should either be fixed values or calculable based on experimental conditions. In the current study, we test observer models for several sizes of three types of targets (rectangular, Gaussian, or Gabor) at two uniform background luminances and three levels of added Gaussian noise. The ideal observer predictions for each individual experimental condition are well correlated with measured d' values (r2 > 0.90 in most cases); however, the required internal noise and human efficiency vary substantially with target and luminance. A modified ideal observer, which includes a luminance-dependent eye filter and Gabor channels, is developed to simultaneously account for the measured d' values in all experimental conditions with r2 = 0.88. This observer model can be used to estimate general target detectability in flat two-dimensional image areas.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jian Yang and Cathleen Daniels Cerosaletti "Observer models and human visual detection performance with different targets", Proc. SPIE 5372, Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment, (4 May 2004); https://doi.org/10.1117/12.535748
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Target detection

Eye models

Visual process modeling

Data modeling

Visualization

Performance modeling

Eye

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