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DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression

Abstract: 

We propose a new architecture for distributed image compression from a group of distributed data sources. The work is motivated by practical needs of data-driven codec design, low power consumption, robustness, and data privacy. The proposed architecture, which we refer to as Distributed Recurrent Autoencoder for Scalable Image Compression (DRASIC), is able to train distributed encoders and one joint decoder on correlated data sources. Its compression capability is much better than the method of training codecs separately. Meanwhile, the performance of our distributed system with 10 distributed sources is only within 2 dB peak signal-to-noise ratio (PSNR) of the performance of a single codec trained with all data sources. We experiment distributed sources with different correlations and show how our data-driven methodology well matches the Slepian-Wolf Theorem in Distributed Source Coding (DSC). To the best of our knowledge, this is the first data-driven DSC framework for general distributed code design with deep learning.

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Paper Details

Authors:
Jie Ding, Vahid Tarokh
Submitted On:
26 March 2020 - 8:33pm
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Enmao Diao
Session:
Session 1
Document Year:
2020
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Document Files

DRASIC Distributed Recurrent Autoencoder for Scalable Image Compression.pdf

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[1] Jie Ding, Vahid Tarokh, "DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5035. Accessed: Sep. 29, 2020.
@article{5035-20,
url = {http://sigport.org/5035},
author = {Jie Ding; Vahid Tarokh },
publisher = {IEEE SigPort},
title = {DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression},
year = {2020} }
TY - EJOUR
T1 - DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression
AU - Jie Ding; Vahid Tarokh
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5035
ER -
Jie Ding, Vahid Tarokh. (2020). DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression. IEEE SigPort. http://sigport.org/5035
Jie Ding, Vahid Tarokh, 2020. DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression. Available at: http://sigport.org/5035.
Jie Ding, Vahid Tarokh. (2020). "DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression." Web.
1. Jie Ding, Vahid Tarokh. DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5035