Hybrid compressive spectral imaging with coded aperture optimization based on coherence minimization

Abstract

Compressive spectral imaging (CSI) obtains spectral images through reconstruction from under-sampled low-dimensional projections with spatial and spectral coding. However, the simultaneous realization of high spatial–spectral resolution is challenged due to limitations of a single CSI architecture. In this paper, a hybrid CSI system combining the coded aperture snapshot spectral imaging (CASSI) and the spectrometer-based single-pixel spectral imaging (SPSI), with the corresponding coded aperture optimization for both constituent systems are proposed. The hybrid CSI system sustains the complementary advantages of the spatial resolution in CASSI and the spectral fidelity in SPSI, ensuring high reconstruction quality in both spatial and spectral dimensions with increased sampling efficiency. The derivable matrix operation of the hybrid CSI system is formulated; meanwhile, based on coherence minimization, the individual optimization on the coded apertures in the CASSI or the SPSI system, and the joint optimization on the coded apertures in the hybrid system are demonstrated. The reconstruction is further improved with the optimization, indicated by the quantitative image quality metrics and the point spectra. Compared to the conventional unoptimized CASSI, the optimized hybrid CSI system improves the PSNR for more than 7 dB. This work may introduce opportunities for multipath compressive imaging systems toward high-efficiency, high-resolution future.