A universal and effective variational method for destriping: application to light-sheet microscopy, FIB-SEM, and remote sensing images

Stripe artifacts are a common problem for various imaging techniques such as light-sheet fluorescence microscopy (LSFM), electron microscopy, and remote sensing. These artifacts are characterized by their elongated shapes, compromised image quality, and impede further analysis. To address the primary challenge of removing the stripe artifacts while preserving the object structures we present an improved variational method for stripe removal with intuitive parametrization. Comparison against previously published methods on images from LSFM, FIB-SEM, and remote sensing by visual inspection and quantitative metrics demonstrates the superior capability of the approach. Based on synthetic LSFM data obtained by simulation of physical light-propagation we enriched our analysis by the comparison of processed images to ground truth data and quantitatively confirmed that our method outperforms existing solutions in terms of improved removal of artifacts and retention of image structures. The open availability of our solution and the flexibility in handling variations in stripe orientation and thickness ensure its broad applicability across diverse imaging scenarios.