Compressive hyperspectral Raman imaging via randomly interleaved scattering projection

Recently, compressive sensing has been introduced to confocal Raman imaging to accelerate data acquisition. In particular, unsupervised compressive imaging methods do not require a priori knowledge of an object's spectral signatures, and they are thus applicable to unknown or dynamically changing systems. However, the current methods based on either spatial or spectral undersampling struggle between spatial and spectral fidelities at high compression ratios. By exciting a sample with an array of focused laser beams and randomly interleaving the projection locations of the scattering, we simultaneously demonstrate a single-acquisition confocal Raman hyperspectral imaging with a high fidelity and resolution in spatial and spectral domains, at a compression ratio of 40-50. The proposed method is also demonstrated with suppressed noise and a smooth transition at the boundaries. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.