Biomedical Imaging GroupSTI
English only   BIG > Publications > Superresolution Microscopy

 Home Page
 News & Events
 Tutorials and Reviews
 Download Algorithms

 All BibTeX References

Grid-Free Localization Algorithm Using Low-Rank Hankel Matrix for Super-Resolution Microscopy

J. Min, K.H. Jin, M. Unser, J.C. Ye

IEEE Transactions on Image Processing, vol. 27, no. 10, pp. 4771-4786, October 2018.

Localization microscopy, such as STORM/PALM, can reconstruct super-resolution images with a nanometer resolution through the iterative localization of fluorescence molecules. Recent studies in this area have focused mainly on the localization of densely activated molecules to improve temporal resolutions. However, higher density imaging requires an advanced algorithm that can resolve closely spaced molecules. Accordingly, sparsity-driven methods have been studied extensively. One of the major limitations of existing sparsity-driven approaches is the need for a fine sampling grid or for Taylor series approximation which may result in some degree of localization bias toward the grid. In addition, prior knowledge of the point-spread function (PSF) is required. To address these drawbacks, here we propose a true grid-free localization algorithm with adaptive PSF estimation. Specifically, based on the observation that sparsity in the spatial domain implies a low rank in the Fourier domain, the proposed method converts source localization problems into Fourier-domain signal processing problems so that a truly grid-free localization is possible. We verify the performance of the newly proposed method with several numerical simulations and a live-cell imaging experiment.

AUTHOR="Min, J. and Jin, K.H. and Unser, M. and Ye, J.C.",
TITLE="Grid-Free Localization Algorithm Using Low-Rank {H}ankel Matrix
        for Super-Resolution Microscopy",
JOURNAL="{IEEE} Transactions on Image Processing",

© 2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from IEEE.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.