Spectroscopic stimulated Raman scattering (SRS) imaging generates chemical maps of intrinsic molecules,with no need for prior knowledge.Despite great advances in instrumentation,the acquisition speed for a spectroscopic SRS image stack is fundamentally bounded by the pixel integration time.In this work,we report three-dimensional sparsely sampled spectroscopic SRS imaging that measures ～ 20％ of pixels throughout the stack.In conjunction with related work in low-rank matrix completion (e.g.,the Netflix Prize),we develop a regularized non-negative matrix factorization algorithm to decompose the sub-sampled image stack into spectral signatures and concentration maps.This design enables an acquisition speed of 0.8 s per image stack,with 50 frames in the spectral domain and 40,000 pixels in the spatial domain,which is faster than the conventional raster laser-scanning scheme by one order of magnitude.Such speed allows real-time metabolic imaging of living fungi suspended in a growth medium while effectively maintaining the spatial and spectral resolutions.This work is expected to promote broad application of matrix completion in spectroscopic laser-scanning imaging.