论文标题
快速和高敏性X射线化学成像的子空间建模
Subspace modeling for fast and high-sensitivity X-ray chemical imaging
论文作者
论文摘要
在纳米级上解决形态学化学阶段转化对于各个学科的许多科学和工业应用至关重要。 TXM-XANES成像技术是通过将全场传输X射线显微镜（TXM）和X射线吸收结合在边缘结构（XANES）（XANES）已成为一种新兴工具，它通过获得一系列具有多能量的显微镜图像，该工具具有多能量X射线，并适合获得化学图。然而，由于系统误差和快速获取的暴露照明，它的能力受到信噪比较差的限制。在这项工作中，通过利用TXM-XANES成像数据的固有属性和子空间建模，我们引入了一种简单且强大的DeNoSising方法来提高图像质量，从而实现快速和高敏感性化学成像。对合成数据集和真实数据集进行的广泛实验证明了该方法的出色性能。
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.
