同步辐射红外共聚焦谱学三维成像重建算法研究

3D Imaging Reconstruction Algorithm for Synchrotron Radiation Infrared Confocal Spectroscopy

为获取物质内部成分的三维分布信息,研究了基于同步辐射红外光源的共聚焦三维成像重建算法。采用单点探测器扫描成像的方式,根据同步辐射红外谱学显微共聚焦三维成像的原理及非线性特性,建立了同步辐射红外谱学显微共聚焦三维成像模型;根据该模型的特点建立测试样品的模型,模拟了红外谱学共聚焦三维成像测试,得到了共聚焦三维成像的测试数据;分别使用Levenberg-Marquardt算法和改进型高斯-牛顿算法对使用前向模型模拟采集得到的结果进行重建。结果表明,前向模型中未加入误差时,Levenberg-Marquardt算法可以重建样品的三维信息,在前向模型中加入1%误差时,Levenberg-Marquardt算法重建得到的结果与实际结果偏差较大,而改进型高斯-牛顿算法可以重建样品的三维信息。

In order to achieve the 3D distribution of internal components of the sample, we study the confocal 3D imaging reconstruction algorithm based on the synchrotron radiation infrared source. A confocal 3D imaging model is built by the single point detector scanning imaging on the basis of the principle and no-linear characteristics of synchrotron radiation infrared confocal spectroscopy 3D imaging. Based on the characteristics of the forward model, the model of the test sample （an absorption shell） is established to simulate the infrared confocal spectroscopy 3D imaging measurement process, and the raw data of the infrared confocal spectroscopy 3D imaging is obtained. Levenberg-Marquardt algorithm and the modified Gauss-Newton algorithm are used to reconstruct the sample model data. The reconstruction results show that the Levenberg-Marquardt algorithm can reconstruct the 3D information of the sample when no random noise is added to the forward model. When 1% noise is in the forward model, the reconstruction result of Levenberg-Marquardt algorithm has a relatively large deviation with the actual result, but the reconstruction result of modified Gauss-Newton algorithm is accurate.