Snapshot hyperspectral imaging based on equalization designed DOE

Abstract

Hyperspectral imaging attempts to determine distinctive information in spatial and spectral domain of a target. Over the past few years, hyperspectral imaging systems have developed towards lighter and faster. In phase-coded hyperspectral imaging systems, a better coding aperture design can improve the spectral accuracy relatively. Using wave optics, we post an equalization designed phase-coded aperture to achieve desired equalization point spread functions (PSFs) which provides richer features for subsequent image reconstruction. During the reconstruction of images, our raised hyperspectral reconstruction network, CAFormer, achieves better results than the state-of-the-art networks with less computation by substituting self-attention with channel-attention. Our work revolves around the equalization design of the phase-coded aperture and optimizes the imaging process from three aspects: hardware design, reconstruction algorithm, and PSF calibration. Our work is putting snapshot compact hyperspectral technology closer to a practical application.