Efficient reconstruction of raman spectroscopy imaging based on compressive sensing

Abstract

Raman Spectroscopy Imaging requires long periods of time for the data acquisition and subsequent treatment of the spectral chemical images. Recently, Compressed Sensing (CS) technique has been used satisfactorily in Raman Spectroscopy Imaging, reducing the acquisition time by simultaneously sensing and compressing the underlying Raman spectral signals. The Coded Aperture Snapshot Spectral Imager (CASSI) is an optical architecture that applied effectively the CS technique in Raman Spectroscopy Imaging. The main optical element of CASSI system is a coded aperture, which can transmit or block the information from the underlying scene. The principal design variable in the coded apertures is the percentage of transmissive elements or transmittance. This paper describes the technique of CS in Raman Spectroscopy imaging by using the CASSI system and realizes the selection of the optimal transmittance values of the coded apertures to ensure an efficient recovery of Raman Images. Diverse simulations are performed to determine the Peak Signal to Noise Ratio (PSNR) of the reconstructed Raman data cubes as a function of the transmittance of the coded apertures, the size of the underlying Raman data cubes and the number of projections expressed in terms of the compression ratio.