Accurate single-molecule localization of super-resolution microscopy images using multiscale products

Recently, a class of single-molecule based localization techniques such as the Photo-activated Localization Mi- croscopy (PALM) or the Stochastic Optical Reconstruction Microscopy (STORM) has ingeniously brought light- microscopy beyond the diraction limit. However, as the single-molecule images contain point source objects (which have no clear edges, alignment and usually superimposed to the background), traditional restoration techniques used for industrial vision images do not give satisfactory result on the PALM/STORM dataset. In this work, we apply the multi-scale product of sub-band images resulting from the wavelet transformation, a technique originally used for astronomical image restoration, for the noise ltering and single-molecule detection in the Super-resolution images. This is an extension of the work by J.C Olivo-Marin1 on spot detection in bio- logical images. Experimental results on real and synthetic datasets with ground-truth show that our approach achieves very good detection rates as compared to the QuickPALM or the rapidSTORM software.

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