We investigate the ability of Deep Joint Source-Channel Coding (DeepJSCC) to be relayed in a decode-and-forward setting over noisy channels and in a hybrid mobile multi-hop setting. To measure the performance we use Peak Signal to Noise Ratio (PSNR) and Learned Perceptual Image Patch Similarity (LPIPS), and we compare a baseline ("regular" DeepJSCC) and our proposed method (DeepJSCC + DHD (Deep Hash Distillation)). The motivation behind our model is to improve perceptual quality of reconstructed images.