Diffusion-Aided Joint Source Channel Coding For High Realism Wireless Image Transmission

arXiv:2404.17736v1 Announce Type: cross
Abstract: Deep learning-based joint source-channel coding (deep JSCC) has been demonstrated as an effective approach for wireless image transmission. Nevertheless, current research has concentrated on minimizing a standard distortion metric such as Mean Squared Error (MSE), which does not necessarily improve the perceptual quality. To address this issue, we propose DiffJSCC, a novel framework that leverages pre-trained text-to-image diffusion models to enhance the realism of images transmitted over the channel. The proposed DiffJSCC utilizes prior deep …

arxiv coding cs.cv diffusion eess.sp image type wireless