Anomaly Detection and Localization, A. Frakt
Tomographic data are acquired by strip integrals over the image
domain. The strips are organized into parallel sets at different
angles. Here we show sets of strips at two angles.
This is an image domain view with a random background field and an
anomaly superimposed in the upper left corner.
This is a view of the tomographic data (also called a sinogram)
corresponding to the image domain shown previously. Each column
represents the data collected at a particular angle. The anomaly
corresponds to the black sinusoidal swath running through this image.
Our approach to anomaly detection and localization consists of a
sequence of composite hypothesis tests. The anomaly (corresponding to
one hypothesis) is successively localized by eliminating groups of
hypotheses. In this figure, the shaded composite hypotheses are
retained while the others are discarded. For more details please see
the publications linked to my
Problems with this site should be emailed to firstname.lastname@example.org