Abstract

In addition to the visual information contained in intensity and color, imaging polarimetry allows visual information to be extracted from the polarization of light. 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 (Block Matching 3D). This algorithm, Polarization-BM3D (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 with spectral polarimetry measurements.

Original languageEnglish
Pages (from-to)690-701
Number of pages12
JournalJournal of the Optical Society of America A
Volume35
Issue number4
DOIs
Publication statusPublished - 30 Mar 2018

Bibliographical note

Accepted manuscript in journal's template.

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