Computational Spectral Imaging Based on Compressive Sensing**Supported by the National Major Scientific Instruments Development Project of China under Grant No 2013YQ030595, the National Natural Science Foundation of China under Grant Nos 11675014, 61601442, 61605218, 61474123 and 61575207, the Science and Technology Innovation Foundation of Chinese Academy of Sciences under Grant No CXJJ-16S047, the National Defense Science and Technology Innovation Foundation

Abstract

Spectral imaging is an important tool for a wide variety of applications. We present a technique for spectral imaging using computational imaging pattern based on compressive sensing (CS). The spectral and spatial information is simultaneously obtained using a fiber spectrometer and the spatial light modulation without mechanical scanning. The method allows high-speed, stable, and sub sampling acquisition of spectral data from specimens. The relationship between sampling rate and image quality is discussed and two CS algorithms are compared.