Photonic computing enabled end-to-end image compression and reconstruction with adjustable ratio and high-fidelity.

Abstract

The rapid development of remote sensing, satellite radar, and medical equipment has created an imperative demand for ultra-efficient image compression and reconstruction. We demonstrate an end-to-end image compression and reconstruction approach using an opto-electronic computing processor, achieving orders-of-magnitude higher speed and lower energy consumption than electronic counterparts. Its core is a 32×32 silicon photonic computing chip, which monolithically integrates 32 high-speed modulators, 32 detectors, and a programmable photonic matrix core, co-packaged with all necessary control electronics. Leveraging the photonic core's programmability, the processor generates trainable compressive matrices, enabling adjustable image compression ratios (up to 256×) to meet diverse application needs. Deploying a customized lightweight photonic integrated circuit-oriented network enables high-quality reconstruction of compressed images. Our approach core parts require end-to-end latency of 49.5 ps/pixel while consuming less than 10.6nJ/pixel. This work not only provides a transformative solution for computational image processing but also opens new avenues for photonic computing application.