Denoising Imaging Polarimetry by an Adapted BM3D Method

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 exist...

Full description

Saved in:
Bibliographic Details
Published inarXiv.org
Main Authors Tibbs, Alexander B, Daly, Ilse M, Roberts, Nicholas W, Bull, David R
Format Paper Journal Article
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 16.11.2017
Subjects
Algorithms
Computer Science - Computer Vision and Pattern Recognition
Image degradation
Noise
Noise reduction
Polarimetry
Polarization
Online AccessGet full text

Cover

More Information
Summary: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.
ISSN:2331-8422
DOI:10.48550/arxiv.1711.04853