Video‐Rate Spectral Imaging Based on Diffractive‐Refractive Hybrid Optics

Abstract

With the advancement of computational imaging, a large number of spectral imaging systems based on encoding–decoding have emerged, among which phase‐encoding spectral imaging systems have attracted widespread interest. Conventional phase‐encoding systems suffer from severe image degradation and limited light throughput. To address these challenges and achieve video‐rate spectral imaging with high spatial resolution and spectral accuracy, a novel optical system based on diffractive‐refractive hybrid optics is proposed. Here, a diffractive optical element is employed to perform imaging and dispersion functions, while a rear lens is used to shorten the system's back focal length and reduce the size of the point spread function. Meanwhile, convolutional neural network‐based spectral reconstruction algorithms are employed to reconstruct the spectral data cubes from diffraction blurred images. A compact, cost‐effective, and portable prototype has been constructed, demonstrating the capability to acquire and reconstruct 30 spectral data cubes per second, each with dimensions of in the spectral range of 480–900 nm with a 10 nm spectral interval. The optical system has the potential to broaden the application scope of phase‐encoding spectral imaging systems in various scenarios.