  The simultaneous capture of imaging data at multiple wavelengths across the
electromagnetic spectrum is highly challenging, requiring complex and costly
multispectral image sensors. In this study, we introduce a comprehensive
framework for performing simultaneous multispectral imaging using conventional
image sensors with color filter arrays via numerical demultiplexing of the
color image sensor measurements. A numerical forward model characterizing the
formation of sensor measurements from light spectra hitting the sensor is
constructed based on a comprehensive spectral characterization of the sensor. A
numerical demultiplexer is then learned via non-linear random forest modeling
based on the forward model. Given the learned numerical demultiplexer, one can
then demultiplex simultaneously-acquired measurements made by the image sensor
into reflectance intensities at discrete selectable wavelengths, resulting in a
higher resolution reflectance spectrum. Simulation and real-world experimental
results demonstrate the efficacy of such a method for simultaneous
multispectral imaging.
