Microwave Image Super-Resolution Using Polarization

Most existing super-resolution imaging techniques rely on parametric models, which offer potential for enhancing image resolution. However, the contradiction between algorithmic complexity and real-time imaging requirements makes it difficult for current platform computing power to handle effectively. To address this issue, this paper proposes a SAR super-resolution imaging method based on a novel polarization information processing paradigm. The method primarily utilizes the differences in polarization characteristics between targets to achieve super-resolution. Firstly, a weight vector is introduced into the fully polarimetric SAR signal model to account for the effects of polarization modulation. Secondly, the objective function of polarization modulation is constructed to fully leverage polarization information. Finally, a super-resolution spectrum is created to realize the super-resolution of microwave images. Experiments conducted using public data demonstrate the effectiveness of the proposed method.