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.