Research Team at BIFOLD/ @tuberlin.bsky.social developed a new #hyperspectral image compression model called #HyCASS.
Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
#RemoteSensing #GISchat #AdvancedImaging #EerthObservation #EO #geoObserver
Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
#RemoteSensing #GISchat #AdvancedImaging #EerthObservation #EO #geoObserver
October 31, 2025 at 9:06 AM
Research Team at BIFOLD/ @tuberlin.bsky.social developed a new #hyperspectral image compression model called #HyCASS.
Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
#RemoteSensing #GISchat #AdvancedImaging #EerthObservation #EO #geoObserver
Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
#RemoteSensing #GISchat #AdvancedImaging #EerthObservation #EO #geoObserver
Paper: Adjustable Spatio-Spectral Hyperspectral Image Compression Network ieeexplore.ieee.org/document/112...
Authors: Martin Hermann Paul Fuchs, Behnood Rasti, Begüm Demir
Code: git.tu-berlin.de/rsim/hycass
Authors: Martin Hermann Paul Fuchs, Behnood Rasti, Begüm Demir
Code: git.tu-berlin.de/rsim/hycass
Adjustable Spatio-Spectral Hyperspectral Image Compression Network
With the rapid growth of hyperspectral data archives in remote sensing (RS), the need for efficient storage has become essential, driving significant attention toward learning based hyperspectral imag...
ieeexplore.ieee.org
October 31, 2025 at 9:06 AM
Paper: Adjustable Spatio-Spectral Hyperspectral Image Compression Network ieeexplore.ieee.org/document/112...
Authors: Martin Hermann Paul Fuchs, Behnood Rasti, Begüm Demir
Code: git.tu-berlin.de/rsim/hycass
Authors: Martin Hermann Paul Fuchs, Behnood Rasti, Begüm Demir
Code: git.tu-berlin.de/rsim/hycass
Unlike existing approaches that focus on compressing either the spatial or spectral dimension, HyCASS is designed to flexibly compress both, adapting the trade-off between spatial and spectral fidelity based on the target compression ratio and image resolution.
October 31, 2025 at 9:06 AM
Unlike existing approaches that focus on compressing either the spatial or spectral dimension, HyCASS is designed to flexibly compress both, adapting the trade-off between spatial and spectral fidelity based on the target compression ratio and image resolution.
HyCASS tackles one of the biggest bottlenecks in remote sensing and advanced imaging: efficiently storing and transmitting extremely large hyperspectral datasets without losing critical spatial or spectral information.
October 31, 2025 at 9:06 AM
HyCASS tackles one of the biggest bottlenecks in remote sensing and advanced imaging: efficiently storing and transmitting extremely large hyperspectral datasets without losing critical spatial or spectral information.