Reconstruction algorithms for RGB-based coded aperture snapshot spectral imaging

TY - JOUR

T1 - Reconstruction algorithms for RGB-based coded aperture snapshot spectral imaging

AU - Ma, Jie

AU - Li, Jun Gang

AU - Fan, Xing Yan

AU - Wang, Wen Hao

AU - Yu, Wen Kai

AU - Zhang, An Ning

N1 - Publisher Copyright: © 2026 Elsevier B.V.

PY - 2026/8

Y1 - 2026/8

N2 - In coded aperture snapshot spectral imaging (CASSI), replacing the monochrome detector with a Bayer RGB sensor provides a compact means of enriching the measurements via pixel-wise wavelength selectivity. This modification, however, requires reconstruction methods that are consistent with the resulting color-dependent spectral modulation. In this work, we develop two RGB-aware reconstruction methods, LRSDN-RGB and SPECAT-RGB, by redesigning key components of two representative paradigms: an unfolding-based method (LRSDN) and an end-to-end transformer-based method (SPECAT). Simulation results show that LRSDN-RGB and SPECAT-RGB achieve PSNR improvements of 1.79 dB and 1.91 dB over their monochrome counterparts, respectively. Real measurements captured using a prototype CASSI system further demonstrate the effectiveness of the proposed methods.

AB - In coded aperture snapshot spectral imaging (CASSI), replacing the monochrome detector with a Bayer RGB sensor provides a compact means of enriching the measurements via pixel-wise wavelength selectivity. This modification, however, requires reconstruction methods that are consistent with the resulting color-dependent spectral modulation. In this work, we develop two RGB-aware reconstruction methods, LRSDN-RGB and SPECAT-RGB, by redesigning key components of two representative paradigms: an unfolding-based method (LRSDN) and an end-to-end transformer-based method (SPECAT). Simulation results show that LRSDN-RGB and SPECAT-RGB achieve PSNR improvements of 1.79 dB and 1.91 dB over their monochrome counterparts, respectively. Real measurements captured using a prototype CASSI system further demonstrate the effectiveness of the proposed methods.

KW - Compressive spectral imaging

KW - RGB sensing

KW - Reconstruction algorithms

UR - https://www.scopus.com/pages/publications/105032841109

U2 - 10.1016/j.optcom.2026.133131

DO - 10.1016/j.optcom.2026.133131

M3 - Article

AN - SCOPUS:105032841109

SN - 0030-4018

VL - 610

JO - Optics Communications

JF - Optics Communications

M1 - 133131

ER -