Skip to content

Covariance Estimation and Denoising for Cryo-EM Images (Covariance Wiener Filtering)

Notifications You must be signed in to change notification settings

PrincetonUniversity/cwf_denoise

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

18 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

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 (tbhamre@math.princeton.edu) and Jane (jzhao@cims.nyu.edu).

About

Covariance Estimation and Denoising for Cryo-EM Images (Covariance Wiener Filtering)

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages