Abstract
A novel speckle noise reduction algorithm based on a combination of Anisotropic Diffusion (AD) filtering and Interval Type-II fuzzy system was developed for reducing speckle noise in Optical Coherence Tomography (OCT) images. Unlike regular AD, the Interval Type-II fuzzy based AD algorithm considers the uncertainty in the calculated diffusion coefficient and appropriate adjustments to the coefficient are made. The new algorithm offers flexibility in optimizing the trade-off between the two image metrics: signal-to-noise (SNR) and Edginess, which are directly related to the structure of the imaged object. Application of the Interval Type-II fuzzy AD algorithm to OCT tomograms acquired in-vivo from a human finger tip and human retina show reduction in the speckle noise with very little edge blurring and about 13 dB and 7 dB image SNR improvement respectively. Comparison with Wiener, Adaptive Lee and regular Anisotropic Diffusion filters, applied to the same images, demonstrates the superior performance of the fuzzy Type-II AD algorithm in terms image SNR and edge preservation metrics improvement.
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