Super-Resolution Imaging and Characterization

Dergan Lin, Purdue University

Abstract: Light in heavily scattering media such as tissue can be modeled with a diffusion equation. A diffusion equation forward model in a computational imaging framework can be used to form images of deep tissue, an approach called diffuse optical tomography, which is important for biomedical studies. However, severe attenuation of high-spatial-frequency information occurs as light propagates through scattering media, limiting image resolution. We introduce a super-resolution approach based on a point emitter localization method that enables a spatial resolution of tens of microns, an improvement of over two orders of magnitude. This is demonstrated experimentally by localizing a small fluorescent inhomogeneity in a slab. Finally, we demonstrate that motion of an object in structured illumination and intensity-based measurements provide sensitivity to material and subwavelength-scale-dimension information. The approach is illustrated as retrieving the refractive index and thickness of a thin film from measured power data as a function of object position.