Reduced-Complexity End-to-End Variational Autoencoder for on Board Satellite Image Compression

Reduced-Complexity End-to-End Variational Autoencoder for on Board Satellite Image Compression

Recently, convolutional neural networks have been successfully applied to lossy image compression. End-to-end optimized autoencoders, possibly variational, are able to dramatically outperform traditional transform coding schemes in terms of rate-distortion trade-off; however, this is at the cost of...

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Bibliographic Details
Main Authors: Vinicius Alves de Oliveira, Marie Chabert, Thomas Oberlin, Charly Poulliat, Mickael Bruno, Christophe Latry, Mikael Carlavan, Simon Henrot, Frederic Falzon, Roberto Camarero
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Remote Sensing
Subjects:
remote sensing
lossy compression
on board compression
transform coding
rate-distortion
JPEG2000
Online Access:https://www.mdpi.com/2072-4292/13/3/447

Internet

https://www.mdpi.com/2072-4292/13/3/447

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