Abstract:Light-sheet fluorescence microscopy (LSFM) is used to capture volume images of biological specimens. It offers high contrast deep inside densely fluorescence labelled samples, fast acquisition speed and minimal harmful effects on the sample. However, the resulting images often show strong stripe artifacts originating from light-matter interactions. We propose a robust variational method suitable for removing stripes which outperforms existing methods and offers flexibility through two adjustable parameters. This tool is widely applicable to improve visual quality as well as facilitate downstream processing and analysis of images acquired on systems that do not provide hardware-based destriping methods. An evaluation of methods is performed on LSFM, FIB-SEM and remote sensing data, supplemented by synthetic LSFM images. The latter is obtained by simulating the imaging process on virtual samples.