On-Board Characterization Of Hyperspectral Image Exposure And Cloud Coverage By Compression Ratio-Reference-Cited by-同舟云学术

On-Board Characterization Of Hyperspectral Image Exposure And Cloud Coverage By Compression Ratio

Published:2022-09-13 Issue: Volume: Page:
ISSN:
Container-title:2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
language:
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Author:

Birkeland R.¹,Berg S.¹,Orlandic M.¹,Garrett J. L.¹

Affiliation:

1. Norwegian University of Science and Technology,Department of Electronic Systems, O. S. Bragstad plass 2A,Trondheim,Norway,N-7034

Funder

Equinor

DNV GL

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9955031/9955024/09955117.pdf?arnumber=9955117

Reference10 articles.

1. In-orbit demonstration of the first hyperspectral imager for nanosatellites

2. Ocean color hyperspectral remote sensing with high resolution and low latency–the hypso-1 cubesat mission;grøtte;IEEE Transactions on Geoscience and Remote Sensing,2021

3. Design of a hyperspectral imager using COTS optics for small satellite applications

4. Estimation of Number of Spectrally Distinct Signal Sources in Hyperspectral Imagery

5. Aalto-1, multi-payload CubeSat: In-orbit results and lessons learned

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1. Onboard Hyperspectral Classification Enables Georeferencing;2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS);2023-10-31

2. Ground systems software for automatic operation of the HYPSO-2 hyperspectral imaging satellite;Sensors, Systems, and Next-Generation Satellites XXVII;2023-10-19

3. Graph neural network-based remote target classification in hyperspectral imaging;International Journal of Remote Sensing;2023-07-18

4. HYPSO-1 CubeSat: First Images and In-Orbit Characterization;Remote Sensing;2023-01-28