Significance: Hyperspectral microscopy has been intensively explored in biomedical applications. However, due to its huge three-dimensional hyperspectral data cube, it typically suffers from slow data acquisition, mass data transmission and storage, and computationally expensive postprocessing.
Aim: To overcome the above limitations, a programmable hyperspectral microscopy technique was developed, which can perform hardware-based hyperspectral data postprocessing by the physical process of optical imaging in a snapshot.
Approach: A programmable hyperspectral microscopy system was developed to collect coded microscopic images from samples under multiplexed illumination. Principal component analysis followed by linear discriminant analysis scheme was coded into multiplexed illumination and realized by the physical process of optical imaging. The contrast enhancement was evaluated on two representative types of microscopic samples, i.e., tissue section and cell samples.
Results: Compared to the microscopic images collected under white light illumination, the contrasts of coded microscopic images were significantly improved by 41% and 59% for tissue section and cell samples, respectively.
Conclusions: The proposed method can perform hyperspectral data acquisition and postprocessing simultaneously by its physical process, while preserving the most important spectral information to maximize the difference between the target and background, thus opening a new avenue for high-contrast microscopic imaging in a snapshot.
Keywords: hyperspectral microscopy; linear discriminant analysis; multiplexed illumination; principal component analysis; programmable optical filter.