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Signal Dependent Non-Linearity Calibration of an Imaging Spectrometer

Baumgartner, Andreas and Schwarzmaier, Thomas (2023) Signal Dependent Non-Linearity Calibration of an Imaging Spectrometer. NEWRAD 2023, 2023-09-11 - 2023-09-15, Teddington, United Kingdom.

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Abstract

We show the signal dependent non-linearity calibration of a HySpex VNIR-1600 hyperspectral sensor using the light addition method. The method has the advantage that a wide spectral range can be calibrated simultaneously with high accuracy. We developed a new setup that uses two lamps, which are coupled into an integrating sphere. The setup can illuminate the whole field of view simultaneously. Additionally, we enhanced the method to allow a denser sampling of the calibration curve than conventionally possible. The results show non-linearities up to 15% dependent on the detector area. After correction, the remaining error is negligible.

Item URL in elib:https://elib.dlr.de/198597/
Document Type:Conference or Workshop Item (Poster)
Title:Signal Dependent Non-Linearity Calibration of an Imaging Spectrometer
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Baumgartner, AndreasUNSPECIFIEDhttps://orcid.org/0000-0002-8495-5407145874840
Schwarzmaier, ThomasUNSPECIFIEDhttps://orcid.org/0000-0003-0475-4400UNSPECIFIED
Date:September 2023
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Calibration, Non-linearity, Imaging spectrometer, HySpex, CHB
Event Title:NEWRAD 2023
Event Location:Teddington, United Kingdom
Event Type:international Conference
Event Start Date:11 September 2023
Event End Date:15 September 2023
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Optical remote sensing
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Experimental Methods
Deposited By: Baumgartner, Andreas
Deposited On:03 Nov 2023 09:45
Last Modified:24 Apr 2024 20:59

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