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Title: Removing Stripes, Scratches, and Curtaining with Nonrecoverable Compressed Sensing

Abstract

Highly-directional image artifacts such as ion mill curtaining, mechanical scratches, or image striping from beam instability degrade the interpretability of micrographs. These unwanted, aperiodic features extend the image along a primary direction and occupy a small wedge of information in Fourier space. Deleting this wedge of data replaces stripes, scratches, or curtaining, with more complex streaking and blurring artifacts—known within the tomography community as “missing wedge” artifacts. Here, we overcome this problem by recovering the missing region using total variation minimization, which leverages image sparsity-based reconstruction techniques—colloquially referred to as compressed sensing (CS)—to reliably restore images corrupted by stripe-like features. Our approach removes beam instability, ion mill curtaining, mechanical scratches, or any stripe features and remains robust at low signal-to-noise. In conclusion, the success of this approach is achieved by exploiting CS's inability to recover directional structures that are highly localized and missing in Fourier Space.

Authors:
ORCiD logo [1];  [2];  [1];  [1];  [1];  [3];  [1];  [3];  [1]
  1. Univ. of Michigan, Ann Arbor, MI (United States)
  2. Argonne National Lab. (ANL), Argonne, IL (United States)
  3. McMaster Univ., Hamilton, ON (Canada)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1572085
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Accepted Manuscript
Journal Name:
Microscopy and Microanalysis
Additional Journal Information:
Journal Volume: 25; Journal Issue: 3; Journal ID: ISSN 1431-9276
Publisher:
Microscopy Society of America (MSA)
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION; FIB tomography; compressed sensing; destriping; electron microscopy; electron tomography

Citation Formats

Schwartz, Jonathan, Jiang, Yi, Wang, Yongjie, Aiello, Anthony, Bhattacharya, Pallab, Yuan, Hui, Mi, Zetian, Bassim, Nabil, and Hovden, Robert. Removing Stripes, Scratches, and Curtaining with Nonrecoverable Compressed Sensing. United States: N. p., 2019. Web. doi:10.1017/S1431927619000254.
Schwartz, Jonathan, Jiang, Yi, Wang, Yongjie, Aiello, Anthony, Bhattacharya, Pallab, Yuan, Hui, Mi, Zetian, Bassim, Nabil, & Hovden, Robert. Removing Stripes, Scratches, and Curtaining with Nonrecoverable Compressed Sensing. United States. doi:10.1017/S1431927619000254.
Schwartz, Jonathan, Jiang, Yi, Wang, Yongjie, Aiello, Anthony, Bhattacharya, Pallab, Yuan, Hui, Mi, Zetian, Bassim, Nabil, and Hovden, Robert. Thu . "Removing Stripes, Scratches, and Curtaining with Nonrecoverable Compressed Sensing". United States. doi:10.1017/S1431927619000254.
@article{osti_1572085,
title = {Removing Stripes, Scratches, and Curtaining with Nonrecoverable Compressed Sensing},
author = {Schwartz, Jonathan and Jiang, Yi and Wang, Yongjie and Aiello, Anthony and Bhattacharya, Pallab and Yuan, Hui and Mi, Zetian and Bassim, Nabil and Hovden, Robert},
abstractNote = {Highly-directional image artifacts such as ion mill curtaining, mechanical scratches, or image striping from beam instability degrade the interpretability of micrographs. These unwanted, aperiodic features extend the image along a primary direction and occupy a small wedge of information in Fourier space. Deleting this wedge of data replaces stripes, scratches, or curtaining, with more complex streaking and blurring artifacts—known within the tomography community as “missing wedge” artifacts. Here, we overcome this problem by recovering the missing region using total variation minimization, which leverages image sparsity-based reconstruction techniques—colloquially referred to as compressed sensing (CS)—to reliably restore images corrupted by stripe-like features. Our approach removes beam instability, ion mill curtaining, mechanical scratches, or any stripe features and remains robust at low signal-to-noise. In conclusion, the success of this approach is achieved by exploiting CS's inability to recover directional structures that are highly localized and missing in Fourier Space.},
doi = {10.1017/S1431927619000254},
journal = {Microscopy and Microanalysis},
number = 3,
volume = 25,
place = {United States},
year = {2019},
month = {3}
}

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