Resolution improvement in real-time and video mosaicing for fiber bundle imaging

Abstract

A fiber bundle allows easy access to a wide range of human tissue. It has smaller diameters, which limits its effective field of view (FOV), and consists of a large number of cores surrounded by a cladding layer, which reduces its spatial resolution. In this paper, we develop an algorithm that processes successively captured raw fiber bundle images in an online fashion. Our algorithm tackles the tasks of super-resolution (SR) and video mosaicing jointly. The natural movement of the fiber tip in successive frames produces offsets that are random in the pixel domain to apply multi-frame SR imaging. Meanwhile, the associated FOV can be extended by mosaicing reconstructed SR images with obtained shifted information. Our approach has low computational complexity that allows for processing in real-time. The performance of resolution improvement in real-time and video mosaicing is demonstrated on the resolution target and biological samples.