Contribution to a conference proceedings

FZJ-2022-04121

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Bad pixel detection for on-board data quality improvement of remote sensing instruments in CubeSats

Florczak, J. (Corresponding author)FZJ* ; Ntokas, K.FZJ* ; Neubert, T.FZJ* ; Zimmermann, E.FZJ* ; Rongen, H.FZJ* ; Clemens, U.FZJ* ; Kaufmann, M.FZJ* ; Riese, M.FZJ* ; van Waasen, S.FZJ*

2022
SPIE

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Please use a persistent id in citations: http://hdl.handle.net/2128/32316  doi:10.1117/12.2633124

Abstract: Large commercial of the shelf pixel arrays in current remote sensing instruments used in CubeSats make on-board processing increasingly important and enables data improvement. Therefore, we first consider the individual steps of the adapted bad pixel detection algorithm - ISMFD. In particular, we consider pixel-to-pixel variations and temporal flickering of pixels in commercial of the shelf sCMOS imaging sensors. We were able to detect an increase of bad pixels from (2.05±0.01)% to (4.1±0.1)% using real measurement images of the flying remote sensing instrument AtmoSHINE. A preliminary implemented adaptive on-board binning method was able to achieve a constant signal-to-noise-ratio on an image with a dynamic light intensity. The additional consideration of bad pixels in the binning method could demonstrate the achievement of data quality of the future remote sensing instrument AtmoLITE.

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Contributing Institute(s):

1. Zentralinstitut für Elektronik (ZEA-2)
2. Stratosphäre (IEK-7)

Research Program(s):

1. 2112 - Climate Feedbacks (POF4-211) (POF4-211)

Appears in the scientific report 2022

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Database coverage:

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