High light efficiency snapshot spectral imaging via spatial multiplexing and spectral mixing

Computational photography has been striving to capture the spectral information of the dynamic world in the last few decades. However, due to the curse of dimensionality between the 3D spectral images and the 2D imaging sensors, light-blocking components, e.g., bandpass filters or coded apertures, have to be used in spectral imaging systems to project the 3D signal into 2D measurements selectively. Accordingly, computational reconstruction is integrated to recover the underlying 3D signal. Thus, these systems suffer from low light efficiency and high computational burden, both of which cannot afford dynamic spectral imaging. In this paper, we propose a novel snapshot spectral imaging system that can dynamically capture the spectral images. The system is composed of a lens array, a notch filter array, and a monochrome camera in principle. Incoming light beams from the scene are spatially multiplexed by the lens array, spectrally mixed by the notch filter array, and captured by the monochrome camera. The two distinct characteristics, i.e., spatial multiplexing and spectral mixing, guarantee the advantages of low computational burden and high light efficiency, respectively. We further build a prototype system according to the imaging principles. The system can record two kinds of images in a single snapshot: bandstop multispectral images and a panchromatic image, which are used jointly to recover the bandpass multispectral images at few computational costs. Moreover, the proposed system is friendly with spectral super-resolution, for which we develop a theoretical demonstration. Both simulations and experiments are conducted to verify the effectiveness of the proposed system.