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Covariance Estimation and Denoising for Cryo-EM Images (Covariance Wiener Filtering)
This project forked from princetonuniversity/cwf_denoise
Covariance Estimation and Denoising for Cryo-EM Images (Covariance Wiener Filtering)
This is a MATLAB package for denoising CTF -affected cryo-EM images based on the following manuscripts: 1) Denoising and Covariance Estimation of Single Particle Cryo-EM Images Tejal Bhamre, Teng Zhang, Amit Singer http://arxiv.org/abs/1602.06632 2) Fast Steerable Principal Component Analysis Zhizhen Zhao, Yoel Shkolnisky, Amit Singer http://arxiv.org/abs/1412.0781 The folder kn_rankest includes code for rank estimation by S. Kritchman and B. Nadler. DEPENDENCIES ---------------- This package should be used in conjunction with the cryo-EM tool box ASPIRE (http://spr.math.princeton.edu/) and will be included in the latest version of ASPIRE. It also requires the NUFFT package (to be included in the latest version of ASPIRE) available at http://www.cims.nyu.edu/cmcl/nufft/nufft.html. INSTRUCTIONS ---------------- 1) Download and install ASPIRE from http://spr.math.princeton.edu/ following the instructions for installation. 2) Add ASPIRE files in your MATLAB path using initpath.m in ASPIRE. 3) If this package is in a separate location than ASPIRE, add the package to your MATLAB path using cwf_paths.m 4) Enjoy the example simulation scripts in cwf_scripts to denoise images. In case of issues or questions, please email Tejal ([email protected]) and Jane ([email protected]).
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