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.
This article is part of the series Advances in Intelligent Vision Systems: Methods and ApplicationsPart II.
A Statistical Detection of an Anomaly from a Few Noisy Tomographic Projections
ISTIT, FRE CNRS 2732, Université de Technologie de Troyes, 12 rue Marie Curie, BP 2060, Troyes Cedex 10010, France
EURASIP Journal on Advances in Signal Processing 2005, 2005:620167 doi:10.1155/ASP.2005.2215
The electronic version of this article is the complete one and can be found online at: http://asp.eurasipjournals.com/content/2005/14/620167
|Received:||1 January 2004|
|Revisions received:||19 November 2004|
|Published:||25 August 2005|
© 2005 Fillatre and Nikiforov