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Optics Letters

Optics Letters


  • Vol. 24, Iss. 20 — Oct. 15, 1999
  • pp: 1383–1385

Improved robustness of target location in nonhomogeneous backgrounds by use of the maximum-likelihood ratio test location algorithm

Vincent Pagé, François Goudail, and Ph. Réfrégier  »View Author Affiliations

Optics Letters, Vol. 24, Issue 20, pp. 1383-1385 (1999)

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We address the problem of localizing small targets with random gray levels that appear in random background clutter. We consider the recently proposed maximum-likelihood ratio test (MLRT) algorithm, which scans the observed scene with an estimation window in which the local statistics are estimated. In the presence of a spatially homogeneous background, we show that if the estimation window is a few times larger than the target itself, the MLRT is quasi-equivalent to the optimal maximum-likelihood (ML) algorithm, which uses the whole scene for estimating the background statistics. The MLRT thus constitutes an efficient alternative to the ML algorithm and is more robust in dealing with spatially nonhomogeneous clutter since it utilizes a small estimation window.

© 1999 Optical Society of America

OCIS Codes
(100.2960) Image processing : Image analysis
(100.5010) Image processing : Pattern recognition
(110.4280) Imaging systems : Noise in imaging systems

Vincent Pagé, François Goudail, and Ph. Réfrégier, "Improved robustness of target location in nonhomogeneous backgrounds by use of the maximum-likelihood ratio test location algorithm," Opt. Lett. 24, 1383-1385 (1999)

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