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A new method in imaging spectrometry

机译:成像光谱学的新方法

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摘要

This new technique for imaging spectrometry is based on computed-tomography (CT). The obvious feature of this method comparing with other imaging spectrometry is its optical system. Two cylindrical lenses compress a two-dimensional object into a one-dimensional image. Subsequently, the spectral image dispersed by a grating is obtained by two-dimensional detector array. A rotation scanning could collect a series of spectral images with different projection angles. The spectral image of the object is reconstructed from these projection images by computed-tomography algorithm. Although this method still needs a rotation scanning to obtain enough information for giving out the data cube of the object, its energy efficiency, and its signal to noise, could be improved significantly. The optical and mathematical theories of this method are discussed. And the suggested optical configuration has also given. A discrete model of this imaging spectrometric system is established to show the digital reconstruction algorithms. A computer simulation based on the discrete model is executed by MATLAB. The reconstructed results with a defined spectral image indicate that the method is capable of reconstructing scenes containing both broadband samples and narrow-band samples. When the specific noise is added, the impact of the number of projection angles on reconstruction precision is analyzed.
机译:这项用于成像光谱的新技术基于计算机断层扫描(CT)。该方法与其他成像光谱法相比的明显特征是其光学系统。两个圆柱透镜将二维物体压缩为一维图像。随后,通过二维检测器阵列获得由光栅分散的光谱图像。旋转扫描可以收集具有不同投影角度的一系列光谱图像。通过计算机断层摄影算法从这些投影图像中重建出物体的光谱图像。尽管此方法仍需要旋转扫描以获得足够的信息以给出对象的数据立方体,但可以显着提高其能量效率和信噪比。讨论了该方法的光学和数学理论。并给出了建议的光学配置。建立该成像光谱系统的离散模型以显示数字重建算法。 MATLAB进行了基于离散模型的计算机仿真。具有定义的光谱图像的重建结果表明该方法能够重建包含宽带样本和窄带样本的场景。当添加特定噪声时,分析了投影角度数量对重建精度的影响。

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