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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. 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.  more » « less
Award ID(s):
1807984
PAR ID:
10106116
Author(s) / Creator(s):
; ; ; ; ; ; ; ;
Date Published:
Journal Name:
Microscopy and Microanalysis
Volume:
25
Issue:
3
ISSN:
1431-9276
Page Range / eLocation ID:
705 to 710
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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