Abstract
Interferometers with a low-coherent illumination allow non-contact evaluating random tissues by locating the visibility maxima of interference fringes. The problem is the light scattering by a tissue, it is why interference fringes are often distorted. Other problem consists in the need to process large amount of data obtained in optical coherence tomography (OCT) imaging systems. We propose to use a stochastic fringe model and Kalman filtering method for noisy low-coherence fringe processing. A fringe signal value is predicted at a next discretization step using full information available before this step and a prediction error is used for dynamic correction of fringe envelope and phase. The advantages of Kalman filtering method consist in its noise-immunity, high-speed data processing and optimal evaluation of fringe parameters. Several specially fabricated wood fiber tissues have been measured with a low-coherence interferometer. The obtained data from the tissue internal structure are evaluated using a dynamic stochastic fringe processing algorithm applied to fringe signal samples series. The statistical approach for characterizing wood fiber tissues of different kinds is proposed.