Fig. 4

Compressive CRS micro-spectroscopy. a Setup of compressive spectral SRS. b Programmable spectral filter using DMD, which can be either programmed for conventional raster scanning or multiplex compressive sensing using a Hadamard basis. Quantification of spectral fidelity between full sampling and compressive sensing at different compression rates is shown. c Setup of compressive FT-CARS. d Comparison between compressive sensing, sparse sampling interpolation and fully sampled spectrum. e Setup of compressive hyperspectral SRS based on matrix completion. f Laser scanning and frequency tuning using 3D triangular Lissajous trajectory. Sampled pixels from three spectrally adjacent frames are projected and color-indexed. g Model-based matrix factorization algorithm to decompose sparsely sampled hyperspectral SRS image into concentration maps and spectra of pure components. a–b are from reference [68], c–d are from reference [69] and e–g are from reference [59]