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Quality Metrics for Imaging Displays (Albert J. Ahumada, Jr.)
Problem

For visibility in bad weather and when windows are not practical, there was an increasing interest in providing pilots with imaging displays from sensors. Engineers designing such systems needed methods of evaluating whether the quality of the displays would be adequate for their intended application.

Objective

The figure illustrates a simulated noisy runway display with an obstructing aircraft. The technical objective was to provide computer programs that would allow a design engineer to predict whether a pilot would see the obstruction as a function of scene and display parameters.

Figure 1. A simulated noisy runway display with an obstructing aircraft
Figure 1. A simulated noisy runway display with an obstructing aircraft

Approach

Our approach was to assume that the engineer can generate a pair of simulated image sequences that are identical except that one has a target and one does not. We would then provide a program that predicts the probability that a person can see the difference between the two image sequences. This laboratory developed several general algorithms for this purpose. The focus of the project was to validate the algorithms for the types of imagery that imaging sensors would generate and develop computationally practical versions of these algorithms.

Accomplishment

Programs have been developed and validated for measuring the visibility of the difference between a pair of static, monochrome images. These models were particularly successful when noise dominates the masking of the target.

Further improvements were made to the masking algorithms to better predict effects of arbitrary background masking.

References

A.J. Ahumada, Jr., A.B. Watson, A.M. Rohaly (1995) Models of human image discrimination predict object detection in natural backgrounds, in B. Rogowitz and J. Allebach, eds., Human Vision, Visual Processing, and Digital Display IV, Proc. Vol. 2411, SPIE, Bellingham, WA, pp. 355-362.

A.B. Watson (1993) Digital Images and Human Vision, MIT Press, Cambridge, MA.

Contact

Albert J. Ahumada, Jr.
(650) 604-6257
Albert.J.Ahumada@nasa.gov
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Curator: Phil So
NASA Official: Brent Beutter
Last Updated: August 15, 2019