Joint ROI Guidance and Spatial Analysis for Task-Aware Distributed Deep Joint Source-Channel Coding

In this paper, we investigate the system performance of deep joint source-channel coding (JSCC) for task-oriented transmission in the Wyner-Ziv scenario, i.e., a distributed coding scenario, aiming to improve the image reconstruction performance and task accuracy. Unlike existing deep JSCC based met...

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Vydáno v:IEEE Global Communications Conference (Online) s. 1936 - 1941
Hlavní autoři: Tian, Wenkai, Dong, Biao, Cao, Bin
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 08.12.2024
Témata:
Accuracy
Correlation
Fuses
Global communication
Image coding
Image communication
Image reconstruction
Robustness
Simulation
System performance
ISSN:2576-6813
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Abstract In this paper, we investigate the system performance of deep joint source-channel coding (JSCC) for task-oriented transmission in the Wyner-Ziv scenario, i.e., a distributed coding scenario, aiming to improve the image reconstruction performance and task accuracy. Unlike existing deep JSCC based methods, we introduce regions of interest (ROI), which facilitates the effective utilization of side information for enhancing task performance. Meanwhile, we incorporate a spatial analysis mechanism to fuse the side information. By integrating these two mechanisms, we propose a novel distributed deep JSCC scheme that further leverages task relevance within the side information. Simulation results show that our proposed scheme outperforms the benchmark in terms of image reconstruction performance and task accuracy. The code is available on the project website 1 .
AbstractList In this paper, we investigate the system performance of deep joint source-channel coding (JSCC) for task-oriented transmission in the Wyner-Ziv scenario, i.e., a distributed coding scenario, aiming to improve the image reconstruction performance and task accuracy. Unlike existing deep JSCC based methods, we introduce regions of interest (ROI), which facilitates the effective utilization of side information for enhancing task performance. Meanwhile, we incorporate a spatial analysis mechanism to fuse the side information. By integrating these two mechanisms, we propose a novel distributed deep JSCC scheme that further leverages task relevance within the side information. Simulation results show that our proposed scheme outperforms the benchmark in terms of image reconstruction performance and task accuracy. The code is available on the project website 1 .
Author Dong, Biao
Cao, Bin
Tian, Wenkai
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  givenname: Bin
  surname: Cao
  fullname: Cao, Bin
  email: caobin@hit.edu.cn
  organization: Harbin Institute Of Technology,School of Electronics and Information Engineering,Shenzhen,China
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SubjectTerms Accuracy
Correlation
Fuses
Global communication
Image coding
Image communication
Image reconstruction
Robustness
Simulation
System performance
Title Joint ROI Guidance and Spatial Analysis for Task-Aware Distributed Deep Joint Source-Channel Coding
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