Extreme Low Bitrate Image Compression System for Mobile Deployment

End-to-end image compression has achieved satisfactory results in recent studies. However, existing methods suffer from high complexity of complicated neural network computation and cannot be directly deployed on mobile devices due to the limitations of computing ability and storage. Therefore, considering the resource and computing ability constrains of the mobile devices, we make a trade-off in this paper between rate-distortion (R-D) performance, inference time, and model complexity. Then we design a novel lightweight perceptual image compression framework to alleviate the storage and complexity burden of mobile devices. Moreover, we design a hardware-friendly deployment scheme to apply the proposed compression framework on high-end mobile devices, which can achieve efficient image compression. Based on the above structures, we propose the first mobile system that achieves image compression on mobile devices. The supplementary material of our system demo is on https://sigport.org/documents/extreme-low-bitrate-Image-compression-system-mobile-deployment.