Deep Joint Source-Channel Coding for Image Transmission with Visual Protection

TL;DR

This paper introduces a deep learning-based joint protection and source-channel coding method for image transmission that effectively safeguards visual content while maintaining high reconstruction quality, addressing security integration challenges in DJSCC.

Contribution

It proposes a novel neural network framework for visual protection integrated with DJSCC, improving security and transmission performance over existing methods.

Findings

Achieves better image reconstruction quality with visual protection.

Successfully couples visual protection with DJSCC in a unified neural network.

Outperforms existing source protection methods in transmission tasks.

Abstract

Joint source-channel coding (JSCC) has achieved great success due to the introduction of deep learning (DL). Compared to traditional separate source-channel coding (SSCC) schemes, the advantages of DL-based JSCC (DJSCC) include high spectrum efficiency, high reconstruction quality, and relief of "cliff effect". However, it is difficult to couple existing secure communication mechanisms (e.g., encryption-decryption mechanism) with DJSCC in contrast with traditional SSCC schemes, which hinders the practical usage of this emerging technology. To this end, our paper proposes a novel method called DL-based joint protection and source-channel coding (DJPSCC) for images that can successfully protect the visual content of the plain image without significantly sacrificing image reconstruction performance. The idea of the design is to use a neural network to conduct visual protection, which converts the plain image to a visually protected one with the consideration of its interaction with DJSCC. During the training stage, the proposed DJPSCC method learns: 1) deep neural networks for image protection and image deprotection, and 2) an effective DJSCC network for image transmission in the protected domain. Compared to existing source protection methods applied with DJSCC transmission, the DJPSCC method achieves much better reconstruction performance.