Translator Disclaimer
4 May 2009 Estimation and detection in degree of polarization images perturbed by detector noise and non uniform illumination
Author Affiliations +
Active imaging systems that illuminate the scene with polarized light and acquire two images in two orthogonal polarizations yield information about the intensity contrast and the Orthogonal State Contrast (OSC) in the scene. However, in real systems, the illumination is often spatially or temporally non uniform. We first study the influence of this non uniformity on estimation performances. We derive the Cramer Rao Lower Bound and determine a profile likelihood-based estimator. We demonstrate the efficiency of this estimator and compare its performance with other standard estimators as a function of the degree of non-uniformity of the illumination. Concerning target detection, illumination non uniformity creates artificial intensity contrasts that can lead to false alarms. We derive the Generalized Likelihood Ratio Test (GLRT) detectors when intensity information is taken into account or not, and determine the relevant expressions of the contrast in these two situations. These results are used to determine in which cases taking intensity information in addition to polarimetric information is relevant or not.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Arnaud Bénière, François Goudail, Mehdi Alouini, and Daniel Dolfi "Estimation and detection in degree of polarization images perturbed by detector noise and non uniform illumination", Proc. SPIE 7335, Automatic Target Recognition XIX, 733510 (4 May 2009);


Atmospheric effects on long stand-off HSI applications
Proceedings of SPIE (May 18 2016)
Results of ACTIM an EDA study on spectral laser...
Proceedings of SPIE (October 05 2011)
ACTIM: an EDA initiated study on spectral active imaging
Proceedings of SPIE (October 08 2010)
Multispectral observations of the surf zone
Proceedings of SPIE (September 11 2003)

Back to Top