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.

The development of the helium ion microscope (HIM) enables the imaging of both hard, inorganic materials and soft, organic or biological materials. Advantages include outstanding topographical contrast, superior resolution down to <0.5 nm at high magnification, high depth of field, and no need for conductive coatings. The instrument relies on helium atom adsorption and ionization at a cryogenically cooled tip that is atomically sharp. Under ideal conditions this arrangement provides a beam of ions that is stable for days to weeks, with beam currents in the order of picoamperes. Over time, however, this stability is lost as gaseous contamination builds up in the source region, leading to adsorbed atoms of species other than helium, which ultimately results in beam current fluctuations. This manifests itself as horizontal stripe artifacts in HIM images. We investigate post-processing methods to remove these artifacts from HIM images, such as median filtering, Gaussian blurring, fast Fourier transforms, and principal component analysis. We arrive at a simple method for completely removing beam current fluctuation effects from HIM images while maintaining the full integrity of the information within the image.