Distributed Image Transmission Using Deep Joint Source-Channel Coding
We study the problem of deep joint source-channel coding (D-JSCC) for correlated image sources, where each source is transmitted through a noisy independent channel to the common receiver. In particular, we consider a pair of images captured by two cameras with probably overlapping fields of view tr...
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| Vydané v: | Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) s. 5208 - 5212 |
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23.05.2022
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| Abstract | We study the problem of deep joint source-channel coding (D-JSCC) for correlated image sources, where each source is transmitted through a noisy independent channel to the common receiver. In particular, we consider a pair of images captured by two cameras with probably overlapping fields of view transmitted over wireless channels and reconstructed in the center node. The challenging problem involves designing a practical code to utilize both source and channel correlations to improve transmission efficiency without additional transmission overhead. To tackle this, we need to consider the common information across two stereo images as well as the differences between two transmission channels. In this case, we propose a deep neural networks solution that includes lightweight edge encoders and a powerful center decoder. Besides, in the decoder, we propose a novel channel state information aware cross attention module to highlight the overlapping fields and leverage the relevance between two noisy feature maps. Our results show the impressive improvement of reconstruction quality in both links by exploiting the noisy representations of the other link. Moreover, the proposed scheme shows competitive results compared to the separated schemes with capacity-achieving channel codes. |
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| AbstractList | We study the problem of deep joint source-channel coding (D-JSCC) for correlated image sources, where each source is transmitted through a noisy independent channel to the common receiver. In particular, we consider a pair of images captured by two cameras with probably overlapping fields of view transmitted over wireless channels and reconstructed in the center node. The challenging problem involves designing a practical code to utilize both source and channel correlations to improve transmission efficiency without additional transmission overhead. To tackle this, we need to consider the common information across two stereo images as well as the differences between two transmission channels. In this case, we propose a deep neural networks solution that includes lightweight edge encoders and a powerful center decoder. Besides, in the decoder, we propose a novel channel state information aware cross attention module to highlight the overlapping fields and leverage the relevance between two noisy feature maps. Our results show the impressive improvement of reconstruction quality in both links by exploiting the noisy representations of the other link. Moreover, the proposed scheme shows competitive results compared to the separated schemes with capacity-achieving channel codes. |
| Author | Wang, Sixian Niu, Kai Dai, Jincheng Yang, Ke |
| Author_xml | – sequence: 1 givenname: Sixian surname: Wang fullname: Wang, Sixian organization: Beijing University of Posts and Telecommunications,Beijing,China,100876 – sequence: 2 givenname: Ke surname: Yang fullname: Yang, Ke organization: Beijing University of Posts and Telecommunications,Beijing,China,100876 – sequence: 3 givenname: Jincheng surname: Dai fullname: Dai, Jincheng organization: Beijing University of Posts and Telecommunications,Beijing,China,100876 – sequence: 4 givenname: Kai surname: Niu fullname: Niu, Kai organization: Beijing University of Posts and Telecommunications,Beijing,China,100876 |
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| Snippet | We study the problem of deep joint source-channel coding (D-JSCC) for correlated image sources, where each source is transmitted through a noisy independent... |
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| SubjectTerms | Codes Decoding deep neural networks Distributed joint source-channel coding Image coding Image communication Noise measurement Speech processing Wireless communication wireless image transmission |
| Title | Distributed Image Transmission Using Deep Joint Source-Channel Coding |
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