Optical data compression and hashing via 4f-based reconfigurable complex convolution module

Here, we introduce an optical computing method using free-space optics and a 4f system to enhance and integrate data processing, encryption, and machine learning. We propose a Reconfigurable Complex Convolution Module (RCCM) which enables simultaneous amplitude and phase modulation of optical signals for complex convolution operations in the Fourier domain. Utilizing spatial light modulators and interferometric techniques based on the Michelson interferometer, the RCCM achieves precise control over light properties. The system demonstrates promising applications in optical hashing, data compression, and accelerating machine learning tasks, particularly for processing encrypted data. Experimental results show the RCCM’s ability to perform complex convolutions with high accuracy, though trade-offs between compression ratios and classification accuracy are observed. This research represents a significant advancement in optical computing, addressing challenges in data security, processing speed, and computational efficiency across various fields.