Statistical algorithms for target detection in coherent active polarimetric images

We address the problem of small-target detection with a polarimetric imager that provides orthogonal state contrast images. Such active systems allow one to measure the degree of polarization of the light backscattered by pur ely depolarizing isotropic materials. To be independent of the spatial nonu niformities of the illumination beam, small-target detection on the orthogo nal state contrast image must be performed without using the image of backs cattered intensity. We thus propose and develop a simple and efficient targ et detection algorithm based on a nonlinear pointwise transformation of the orthogonal state contrast image followed by a maximum-likelihood algorithm optimal for additive Gaussian perturbations. We demonstrate the efficiency of this suboptimal technique in comparison with the optimal one, which, ho wever, assumes a priori knowledge about the scene that is not available in practice. We illustrate the performance of this approach on both simulated and real polarimetric images. (C) 2001 Optical Society of America.