Estimation of Degree of Polarization in Low Light Using Truncated Poisson Distribution

The Degree of Polarization (DoP) of a light beam inside a medium contains unique information about the medium. 3D imaging techniques constitute an optimal procedure for determining the DoP under low light conditions, as the computational reconstruction process can increase the signal-to-noise ratio...
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Autor*in:	Marcos Avinoa [verfasserIn] Xin Shen [verfasserIn] Salvador Bosch [verfasserIn] Bahram Javidi [verfasserIn] Artur Carnicer [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Optical imaging optical physics optical polarization stokes parameters

Übergeordnetes Werk:	In: IEEE Photonics Journal - IEEE, 2015, 14(2022), 3, Seite 8
Übergeordnetes Werk:	volume:14 ; year:2022 ; number:3 ; pages:8

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/JPHOT.2022.3176125

Katalog-ID:	DOAJ02240578X

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callnumber-first	T - Technology
author	Marcos Avinoa
spellingShingle	Marcos Avinoa misc TA1501-1820 misc QC350-467 misc Optical imaging misc optical physics misc optical polarization misc stokes parameters misc Applied optics. Photonics misc Optics. Light Estimation of Degree of Polarization in Low Light Using Truncated Poisson Distribution
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topic_title	TA1501-1820 QC350-467 Estimation of Degree of Polarization in Low Light Using Truncated Poisson Distribution Optical imaging optical physics optical polarization stokes parameters
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title	Estimation of Degree of Polarization in Low Light Using Truncated Poisson Distribution
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title_auth	Estimation of Degree of Polarization in Low Light Using Truncated Poisson Distribution
abstract	The Degree of Polarization (DoP) of a light beam inside a medium contains unique information about the medium. 3D imaging techniques constitute an optimal procedure for determining the DoP under low light conditions, as the computational reconstruction process can increase the signal-to-noise ratio of the detected light. The definition of the DoP contains a division by the total number of detected photons from the sensor. However, under photon starved conditions, the number of detected photons at a single time period may be equal to zero. This may pose a division by zero problem for the computation of DoP. In this work, we consider a truncated Poisson distribution to overcome this problem and show that the mean value of the computed DoP goes to zero independently of the state of polarization of the light. The validity of our approach is verified by capturing the light fields of a test object to compute its DoP under low light conditions. The formulae derived in this work can be used to correct the deviation of the mean value of the DoP with respect to the ideal measurements.
abstractGer	The Degree of Polarization (DoP) of a light beam inside a medium contains unique information about the medium. 3D imaging techniques constitute an optimal procedure for determining the DoP under low light conditions, as the computational reconstruction process can increase the signal-to-noise ratio of the detected light. The definition of the DoP contains a division by the total number of detected photons from the sensor. However, under photon starved conditions, the number of detected photons at a single time period may be equal to zero. This may pose a division by zero problem for the computation of DoP. In this work, we consider a truncated Poisson distribution to overcome this problem and show that the mean value of the computed DoP goes to zero independently of the state of polarization of the light. The validity of our approach is verified by capturing the light fields of a test object to compute its DoP under low light conditions. The formulae derived in this work can be used to correct the deviation of the mean value of the DoP with respect to the ideal measurements.
abstract_unstemmed	The Degree of Polarization (DoP) of a light beam inside a medium contains unique information about the medium. 3D imaging techniques constitute an optimal procedure for determining the DoP under low light conditions, as the computational reconstruction process can increase the signal-to-noise ratio of the detected light. The definition of the DoP contains a division by the total number of detected photons from the sensor. However, under photon starved conditions, the number of detected photons at a single time period may be equal to zero. This may pose a division by zero problem for the computation of DoP. In this work, we consider a truncated Poisson distribution to overcome this problem and show that the mean value of the computed DoP goes to zero independently of the state of polarization of the light. The validity of our approach is verified by capturing the light fields of a test object to compute its DoP under low light conditions. The formulae derived in this work can be used to correct the deviation of the mean value of the DoP with respect to the ideal measurements.
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title_short	Estimation of Degree of Polarization in Low Light Using Truncated Poisson Distribution
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Estimation of Degree of Polarization in Low Light Using Truncated Poisson Distribution

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