Optical light scattering to improve image classification via wavelength division multiplexing

Machine learning is constantly contributing significant progress in many areas while posing huge demands for computing resources. It has been demonstrated the feasibility of leveraging random light scattering to decrease the computational resource demands of image classification algorithms. However, optical devices in optical random scattering systems, such as cameras, constrain the bandwidth of the entire system. In this study, a high-speed scattering system based on wavelength division multiplexing (WDM) was proposed. By employing the high bandwidth semiconductor lasers and quadrant PIN detectors, this WDM scattering system achieves over a 1000-times increase in acquisition speed compared to the traditional camera-based spatial scattering system. Moreover, this WDM scattering system has been demonstrated to improve the classification accuracy for RC on nine datasets, including MNIST, Chest_X-ray, and Malaria, by 26.15%.