Modified robust anisotropic diffusion denoising technique with regularized Richardson-Lucy deconvolution for two-photon microscopic images

Although two-photon fluorescence microscopy has quite good optical sectioning ability, it still suffers from image blurring. The Richardson-Lucy deconvolution algorithm has been routinely employed to reduce image blurring because it is well suited to characterizing the Poisson statistics of the photomultiplier. However, noises are amplified in this iterative procedure, so a denoising technique should be introduced before performing the Richardson-Lucy deconvolution. An algorithm that prefilters undesired noise by modifying the robust anisotropic diffusion before performing the regularized Richardson-Lucy deconvolution is proposed. Experiments have shown that noise is almost eliminated, sharp edges are well preserved, and more details of structures are distinguished with this technique. Quantitative data of four evaluation criteria are provided to validate the performance of the proposed scheme. Lastly, we apply the proposed approach to the image restoration of real two-photon microscopic images.

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