  With the rapid development of Artificial Intelligent Internet of Things
(AIoT), the image data from AIoT devices has been witnessing the explosive
increasing. In this paper, a novel deep image semantic communication model is
proposed for the efficient image communication in AIoT. Particularly, at the
transmitter side, a high-precision image semantic segmentation algorithm is
proposed to extract the semantic information of the image to achieve
significant compression of the image data. At the receiver side, a semantic
image restoration algorithm based on Generative Adversarial Network (GAN) is
proposed to convert the semantic image to a real scene image with detailed
information. Simulation results demonstrate that the proposed image semantic
communication model can improve the image compression ratio and recovery
accuracy by 71.93% and 25.07% on average in comparison with WebP and CycleGAN,
respectively. More importantly, our demo experiment shows that the proposed
model reduces the total delay by 95.26% in the image communication, when
comparing with the original image transmission.
