Subspace modeling for fast and high-sensitivity X-ray chemical imaging

• URL: http://arxiv.org/abs/2201.00259v1
• Date: Sat, 1 Jan 2022 23:26:06 GMT
• Title: Subspace modeling for fast and high-sensitivity X-ray chemical imaging
• Authors: Jizhou Li, Bin Chen, Guibin Zan, Guannan Qian, Piero Pianetta, Yijin Liu
• Abstract summary: The TXM-XANES imaging technique has been an emerging tool which operates by acquiring a series of microscopy images with multi-energy X-rays and fitting to obtain the chemical map. We introduce a simple and robust denoising approach to improve the image quality, which enables fast and high-sensitivity chemical imaging.
• Score: 4.062272647963248
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Resolving morphological chemical phase transformations at the nanoscale is of vital importance to many scientific and industrial applications across various disciplines. The TXM-XANES imaging technique, by combining full field transmission X-ray microscopy (TXM) and X-ray absorption near edge structure (XANES), has been an emerging tool which operates by acquiring a series of microscopy images with multi-energy X-rays and fitting to obtain the chemical map. Its capability, however, is limited by the poor signal-to-noise ratios due to the system errors and low exposure illuminations for fast acquisition. In this work, by exploiting the intrinsic properties and subspace modeling of the TXM-XANES imaging data, we introduce a simple and robust denoising approach to improve the image quality, which enables fast and high-sensitivity chemical imaging. Extensive experiments on both synthetic and real datasets demonstrate the superior performance of the proposed method.

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