摘要翻译：
本文描述了一种共面无创无损电容成像器件。我们首先介绍了它的输出的数学模型，并讨论了它的一些理论能力。我们表明，从该装置获得的数据可以解释为被测物体表面附近的介电常数的加权Radon变换。由实验数据重建的图像提供了良好的表面分辨率和短深度成像，使该设备成为一个2D+1美元的成像器。图像的质量使我们期望通过\emph{ad-hoc}优化的反演公式可以获得出色的结果。还有一些有趣的，但未被探索的，成像理论问题，这个传感器将允许测试。
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英文标题：
《Combining Radon transform and Electrical Capacitance Tomography for a
  $2d+1$ imaging device》
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作者：
Yves Capdeboscq and Hrand Mamigonians and Aslam Sulaimalebbe and Vahe
  Tshitoyan
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Image and Video Processing        图像和视频处理
分类描述：Theory, algorithms, and architectures for the formation, capture, processing, communication, analysis, and display of images, video, and multidimensional signals in a wide variety of applications. Topics of interest include: mathematical, statistical, and perceptual image and video modeling and representation; linear and nonlinear filtering, de-blurring, enhancement, restoration, and reconstruction from degraded, low-resolution or tomographic data; lossless and lossy compression and coding; segmentation, alignment, and recognition; image rendering, visualization, and printing; computational imaging, including ultrasound, tomographic and magnetic resonance imaging; and image and video analysis, synthesis, storage, search and retrieval.
用于图像、视频和多维信号的形成、捕获、处理、通信、分析和显示的理论、算法和体系结构。感兴趣的主题包括：数学，统计，和感知图像和视频建模和表示；线性和非线性滤波、去模糊、增强、恢复和重建退化、低分辨率或层析数据；无损和有损压缩编码；分割、对齐和识别；图像渲染、可视化和打印；计算成像，包括超声、断层和磁共振成像；以及图像和视频的分析、合成、存储、搜索和检索。
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英文摘要：
  This paper describes a coplanar non invasive non destructive capacitive imaging device. We first introduce a mathematical model for its output, and discuss some of its theoretical capabilities. We show that the data obtained from this device can be interpreted as a weighted Radon transform of the electrical permittivity of the measured object near its surface. Image reconstructions from experimental data provide good surface resolution as well as short depth imaging, making the apparatus a $2d+1$ imager. The quality of the images leads us to expect that excellent results can be delivered by \emph{ad-hoc} optimized inversion formulas. There are also interesting, yet unexplored, theoretical questions on imaging that this sensor will allow to test.
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PDF链接：
https://arxiv.org/pdf/1806.11175