Three-dimensional color photon counting microscopy using Bayesian estimation with adaptive priori information

Abstract

In this Letter, we propose a novel three-dimensional (3D) color microscopy for microorganisms under photon-starved conditions using photon counting integral imaging and Bayesian estimation with adaptive priori information. In photon counting integral imaging, 3D images can be visualized using maximum likelihood estimation (MLE). However, since MLE does not consider a priori information of objects, the visual quality of 3D images may not be accurate. In addition, the only grayscale image can be reconstructed. Therefore, to enhance the visual quality of 3D images, we propose photon counting microscopy using maximum a posteriori with adaptive priori information. In addition, we consider a wavelength of each basic color channel to reconstruct 3D color images. To verify our proposed method, we carry out optical experiments.