Single Pixel Spectral Image Fusion with Side Information from a Grayscale Sensor

Compressive spectral imaging (CSI) allows the acquisition of the spectral information of a three dimensional scene by using two dimensional coded projections. However, compressed sampling of information with simultaneously high spatial and high spectral resolution demands expensive highresolution sensors. Single pixel imaging is an approach that has had a high impact in spectroscopy, due to its low-cost implementation compared to architectures with larger sensors. One of the main challenges in CSI is to obtain high quality image reconstructions using low-cost architectures. Recent works have been shown that image fusion using measurements from a CSI sensor based on side information leads to improvement in the quality of the fused image. This work proposes a methodology that combines the spectral information of a single pixel camera (SPC) and the side information of a grayscale sensor in order to improve the reconstruction quality of the spatio-spectral data cube. Simulations and experimental results for the proposed method are shown, and its performance is compared with respect to the traditional approach of upsampling the single pixel image reconstruction through bilinear interpolation.