Cui Qi, Park Jongchan, Iyer Rishyashring R, Žurauskas Mantas, Boppart Stephen A, Smith R Theodore, Gao Liang
Appl Opt. 2020 Jul 10;59(20):6062-6069. doi: 10.1364/AO.395988.
An image mapping spectrometer (IMS) is a snapshot hyperspectral imager that simultaneously captures both the spatial (, ) and spectral () information of incoming light. The IMS maps a three-dimensional (3D) datacube (, , ) to a two-dimensional (2D) detector array (, ) for parallel measurement. To reconstruct the original 3D datacube, one must construct a lookup table that connects voxels in the datacube and pixels in the raw image. Previous calibration methods suffer from either low speed or poor image quality. We herein present a slit-scan calibration method that can significantly reduce the calibration time while maintaining high accuracy. Moreover, we quantitatively analyzed the major artifact in the IMS, the striped image, and developed three numerical methods to correct for it.
图像映射光谱仪（IMS）是一种快照式高光谱成像仪，它能同时捕获入射光的空间（x, y）和光谱（λ）信息。IMS将三维（3D）数据立方体（x, y, λ）映射到二维（2D）探测器阵列（x, y）进行并行测量。为了重建原始的3D数据立方体，必须构建一个查找表，将数据立方体中的体素与原始图像中的像素连接起来。以前的校准方法要么速度慢，要么图像质量差。我们在此提出一种狭缝扫描校准方法，它可以在保持高精度的同时显著减少校准时间。此外，我们对IMS中的主要伪像——条纹图像进行了定量分析，并开发了三种数值方法来对其进行校正。
