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28 results

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  • In situ study of microstructure in phase transformation of pipe line steel

  • Chen Gu, Nabil Bassim, Hatem Zurob
  • Journal:
    Microscopy and Microanalysis / Volume 27 / Issue S1 / August 2021
    Published online by Cambridge University Press:
    30 July 2021, pp. 1554-1555
    Print publication:
    August 2021
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  • Probing Phonon Polaritons Across Nanoscale Gaps

  • Isobel Bicket, Connor Wong, Joshua Tefal, Nabil Bassim, Maureen Joel Lagos
  • Journal:
    Microscopy and Microanalysis / Volume 27 / Issue S1 / August 2021
    Published online by Cambridge University Press:
    30 July 2021, pp. 702-704
    Print publication:
    August 2021
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  • Removing Stripes, Scratches, and Curtaining with Nonrecoverable Compressed Sensing

  • Jonathan Schwartz, Yi Jiang, Yongjie Wang, Anthony Aiello, Pallab Bhattacharya, Hui Yuan, Zetian Mi, Nabil Bassim, Robert Hovden
  • Journal:
    Microscopy and Microanalysis / Volume 25 / Issue 3 / June 2019
    Published online by Cambridge University Press:
    14 March 2019, pp. 705-710
    Print publication:
    June 2019
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  • 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.

  • Multi-Angle Plasma Focused Ion Beam (FIB) Curtaining Artifact Correction Using a Fourier-Based Linear Optimization Model

  • Christopher W. Schankula, Christopher K. Anand, Nabil D. Bassim
  • Journal:
    Microscopy and Microanalysis / Volume 24 / Issue 6 / December 2018
    Published online by Cambridge University Press:
    07 December 2018, pp. 657-666
    Print publication:
    December 2018

  • We present a flexible linear optimization model for correcting multi-angle curtaining effects in plasma focused ion beam scanning electron microscopy (PFIB-SEM) images produced by rocking-polishing schemes. When PFIB-SEM is employed in a serial sectioning tomography workow, it is capable of imaging large three-dimensional volumes quickly, providing rich information in the critical 10–100 nm feature length scale. During tomogram acquisition, a “rocking polish” is often used to reduce straight-line “curtaining” gradations in the milled sample surface. While this mitigation scheme is effective for deep curtains, it leaves shallower line artifacts at two discretized angles. Segmentation and other automated processing of the image set requires that these artifacts be corrected for accurate microstructural quantification. Our work details a new Fourier-based linear optimization model for correcting curtaining artifacts by targeting curtains at two discrete angles. We demonstrate its capabilities by processing images from a tomogram from a multiphase, heterogeneous concrete sample. We present methods for selecting the parameters which meet the user’s goals most appropriately. Compared to previous works, we show that our model provides effective multi-angle curtain correction without introducing artifacts into the image, modifying non-curtain structures or causing changes to the contrast of voids. Our algorithm can be easily parallelized to take advantage of multi-core hardware.

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