Abstract
Fiber imaging bundles allow the transfer of optical images from
place-to-place along narrow and flexible conduits. Traditionally used
extensively in medical endoscopy, bundles are now finding new
applications in endoscopic microscopy and other emerging techniques.
PyFibreBundle is an open-source Python package for fast processing of
images acquired through imaging bundles. This includes detection and
removal of the fiber core pattern by filtering or interpolation, and
application of background and flat-field corrections. It also allows
images to be stitched together to create mosaics and resolution to be
improved by combining multiple shifted images. This paper describes
the technical implementation of PyFibreBundle and provides example
results from three endomicroscopy imaging systems: color transmission,
monochrome transmission, and confocal fluorescence. This allows
various processing options to be compared quantitatively and
qualitatively, and benchmarking demonstrates that PyFibreBundle can
achieve state-of-the-art performance in an open-source package. The
paper demonstrates core removal by interpolation and mosaicing at over
100 fps, real-time multi-frame resolution enhancement and the first
demonstration of real-time endomicroscopy image processing, including
core removal, on a Raspberry Pi single board computer. This
demonstrates that PyFibreBundle is potentially a valuable tool for the
development of low-cost, high-performance fiber bundle imaging
systems.
Subject
Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering
Cited by
3 articles.
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