Generative Joint Source-Channel Coding for Semantic Image Transmission

Recent works have shown that joint source-channel coding (JSCC) schemes using deep neural networks (DNNs), called DeepJSCC, provide promising results in wireless image transmission. However, these methods mostly focus on the distortion of the reconstructed signals with respect to the input image, ra...

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Bibliographic Details
Published in:	IEEE journal on selected areas in communications Vol. 41; no. 8; pp. 2645 - 2657
Main Authors:	Erdemir, Ecenaz, Tung, Tze-Yang, Dragotti, Pier Luigi, Gunduz, Deniz
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.08.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Artificial neural networks Channel coding Coders Compression ratio Distortion Generative adversarial networks Generators Image coding Image reconstruction Image transmission Inverse problems joint source-channel coding Optimization perceptual similarity Semantic communication Semantics Signal to noise ratio StyleGAN Training Wireless communication
ISSN:	0733-8716, 1558-0008
Online Access:	Get full text
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