A median-Gaussian filtering framework for Moiré pattern noise removal from X-ray microscopy image

Moiré pattern noise in Scanning Transmission X-ray Microscopy (STXM) imaging introduces significant errors in qualitative and quantitative image analysis. Due to the complex origin of the noise, it is difficult to avoid Moiré pattern noise during the image data acquisition stage. In this paper, we introduce a post-processing method for filtering Moiré pattern noise from STXM images. This method includes a semi-automatic detection of the spectral peaks in the Fourier amplitude spectrum by using a local median filter, and elimination of the spectral noise peaks using a Gaussian notch filter. The proposed median-Gaussian filtering framework shows good results for STXM images with the size of power of two, if such parameters as threshold, sizes of the median and Gaussian filters, and size of the low frequency window, have been properly selected.

► Moiré pattern noise has occasionally been observed in Scanning Transmission X-ray Microscopy (STXM) images.
► The STXM images with the noise introduce significant errors in image analysis for chemical speciation and quantification of the specimen composition.
► Due to the complex origination of the noise, it is difficult to avoid the Moiré pattern noise during the data acquisition stage.
► In this study, we investigate the feasibility to apply a post-processing method to remove the noise from STXM images.