In three-dimensional (3-D) synthetic aperture radar (SAR) imaging, the elevation reflectivity function of each azimuth-range pixel is typically recovered through a large number of data collected by parallel flight tracks. Especially for holographic SAR (HoloSAR) tomography with high-resolution and panoramic 3-D imaging capabilities, it provides many important features for applications such as urban monitoring and 3-D mapping. In recent years, the utilization of polarimetric SAR data has been found to have tremendous potential in the performance improvement of 3-D reconstruction. In this letter, we propose a novelL2,1-norm based polarimetric HoloSAR imaging method, which utilizes the structural correlation between the echoes acquired from different polarimetric channels to achieve high-quality 3-D scene recovery. Compared with typical spectrum estimation based and compressed sensing (CS) based methods that only consider the single-polarimetric data, the proposed method can improve the accuracy and robustness of 3-D reconstruction. Experimental results based on real GOTCHA dataset verify the feasibility and potential of the proposed method.