A statistical detection of an anomaly from a few noisy tomographic projections

Authors:
Lionel Fillatre;Igor Nikiforov
Affiliations:
ISTIT, FRE CNRS, Université de Technologie de Troyes, Troyes Cedex, France;ISTIT, FRE CNRS, Université de Technologie de Troyes, Troyes Cedex, France
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2005

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Abstract

The problem of detecting an anomaly/target from a very limited number of noisy tomographic projections is addressed from the statistical point of view. The imaged object is composed of an environment, considered as a nuisance parameter, with a possibly hidden anomaly/target. The GLR test is used to solve the problem. When the projection linearly depends on the nuisance parameters, the GLR test coincides with an optimal statistical invariant test.