2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDIVMSP-3.3
Paper Title SNR-ADAPTIVE DEEP JOINT SOURCE-CHANNEL CODING FOR WIRELESS IMAGE TRANSMISSION
Authors Mingze Ding, Harbin Institute of Technology, China; Jiahui Li, Mengyao Ma, Huawei, China; Xiaopeng Fan, Harbin Institute of Technology, China
SessionIVMSP-3: Image & Video Coding 1
LocationGather.Town
Session Time:Tuesday, 08 June, 14:00 - 14:45
Presentation Time:Tuesday, 08 June, 14:00 - 14:45
Presentation Poster
Topic Image, Video, and Multidimensional Signal Processing: [IVCOM] Image & Video Communications
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Considering the problem of joint source-channel coding (JSCC) for multi-user transmission of images over noisy channels, an autoencoder-based novel deep joint source-channel coding scheme is proposed in this paper. In the proposed JSCC scheme, the decoder can estimate the signal-to-noise ratio (SNR) and use it to adaptively decode the transmitted image. Experiments demonstrate that the proposed scheme achieves impressive results in adaptability for different SNRs and is robust to the decoder’s estimation error of the SNR. To the best of our knowledge, this is the first deep JSCC scheme that focuses on the adaptability for different SNRs and can be applied to multi-user scenarios.