Displaying Confidence Images
J. Nagy and D. O'Leary
Algorithms for computing images result in an estimate of an image.
The image may result from deblurring a measured image, from
deconvolving a set of measurements, or from computing an image
by modeling physical processes such as the weather.
These computations provide an estimated value for each pixel
in the image.
What is lacking, however, is an estimate of the statistical confidence
that we can have in those pixel values or in the features they form.
In this work we discuss novel ways to display confidence information,
using an algorithm called {\sf Twinkle}, in order to give the viewer
valuable visual insight into uncertainties.
The technique is useful whether the confidence information
is in the form of a confidence interval or a distribution
of possible values.
We demonstrate how to display confidence information
in a variety of applications: weather forecasts, intensity
of a star, and rating a potential tumor in a diagnostic image.