  Imaging polarimetry allows more information to be extracted from a scene than
conventional intensity or colour imaging. However, a major challenge of imaging
polarimetry is image degradation due to noise. This paper investigates the
mitigation of noise through denoising algorithms and compares existing
denoising algorithms with a new method, based on BM3D. This algorithm, PBM3D,
gives visual quality superior to the state of the art across all images and
noise standard deviations tested. We show that denoising polarization images
using PBM3D allows the degree of polarization to be more accurately calculated
by comparing it to spectroscopy methods.
