Maximum-likelihood estimation of the polarization degree from two multi-look intensity images
Information contained in polarimetric images can be characterized by a scalar parameter called the polarization degree. This parameter is usually estimated using four polarimetric images. However, acquisition and registration of four images are complex and costly. Thus, reducing the number of required images can be of great interest for practical applications. In coherent illumination, these images are degraded by speckle noise. This noise can be reduced by transforming the original single-look images into multi-look images. We provide maximum likelihood estimators of the polarization degree in the general case of multi-look intensity images. The estimators are derived based on only two measurements, under coherent illumination and fully developed speckle. We evaluate our method on synthetic data and compare its performance with that of moment-based methods.