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Estimation and detection in degree of polarization images perturbed by detector noise and non uniform illumination

机译:受检测器噪声和不均匀照明干扰的偏振图像程度的估计和检测

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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.
机译:主动成像系统使用偏振光照射场景并获取两个正交偏振的两个图像,从而产生有关场景中强度对比和正交状态对比度(OSC)的信息。但是,在实际系统中,照明通常在空间或时间上是不均匀的。我们首先研究这种非均匀性对估计性能的影响。我们导出Cramer Rao下界,并确定基于轮廓似然的估计量。我们演示了该估计器的效率,并将其性能与其他标准估计器的性能作比较,该函数是照明不均匀程度的函数。关于目标检测,照明不均匀会产生人为的强度对比,这可能导致错误的警报。我们在不考虑强度信息的情况下得出广义似然比测试(GLRT)检测器,并确定这两种情况下对比度的相关表达式。这些结果用于确定在什么情况下,除了偏振信息外,强度信息是否相关。

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