Evaluation of spatial interpolation strategies for the removal of comb-structure in fiber-optic images.

Modern techniques for medical diagnosis and therapy in minimal invasive surgery scenarios as well as industrial inspection make considerable use of flexible, fiberoptic endoscopes in order to gain visual access to holes, hollows, antrums and cavities that are difficult to enter and examine. Unfortunately, fiber-optic endoscopes exhibit artifacts in the images that hinder or at worst prevent fundamental image analysis techniques. The dark comb-like artifacts originate from the opaque cladding layer surrounding each single fiber in the image conductor. Although the removal of comb structure is crucial for fiber-optic image analysis, literature covers only a few approaches. Those are based on Fourier analysis and make use of spectral masking or they operate in the spatial domain and rely on interpolation. In this paper, we concentrate on the latter type and introduce interpolation concepts known from related disciplines to the task of comb structure removal. For a quantitative evaluation, we perform experiments with real images as well as with bivariate test functions and rate an algorithm's performance in terms of the normalized root mean square error - a quality metric that it is most commonly used in signal processing for this purpose. Hence, this paper counters the fact that literature lacks an objective performance comparison of the state-of-the-art interpolation based approaches for this type of application.