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A snapshot foveal hyperspectral imager

机译:快照中央凹高光谱成像仪

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摘要

We present a new approach to hyperspectral imaging that is inspired by biological imaging systems, such as human vision, which employ high spectral and spatial discrimination only in a small central patch. This foveal technique addresses several problems of conventional approaches to HSI: they cannot provide snapshot, high spectral-resolution imagery in a two dimensional format. The ability to provide the data in a single snapshot removes temporal misregistration issues. High signal to noise ratios naturally result from the absence of any multiplexing technique and the corresponding loss of light. Other reported snapshot techniques are either low spectral resolution or provide only a one-dimensional field of view. A high-spectral-resolution imager with a wide field of view could produce giga-sample data rates, which would make real-time data processing problematic. By gathering hyperspectral data from only a selected portion of the scene, we reduce the data processing rates to manageable levels. For many applications only a small field of view is required, but needs to be cued for situational awareness. In our system, this is provided for by a wide field of view, panchromatic imager, which fills a similar role to peripheral vision hi the biological systems mentioned above. Our technique images the selected region onto a coherent fibre bundle, which reformats the input into a line array constituting the input to a dispersive hyperspectral imager. Computer processing reformats the dispersed one-dimensional output into a rectangular image and applies calibration routines to produce a high spectral resolution, small hyperspectral image. This is combined with a high-spatial-resolution panchromatic image. Experimental results will be presented.
机译:我们提出了一种高光谱成像的新方法,该方法受到生物成像系统(例如人类视觉)的启发,该系统仅在较小的中央斑块中采用高光谱和空间分辨力。这种中心凹技术解决了HSI常规方法的几个问题:它们无法以二维格式提供快照,高光谱分辨率的图像。在单个快照中提供数据的能力消除了时间未对准问题。高信噪比自然是由于没有任何多路复用技术以及相应的光损耗而导致的。其他报告的快照技术要么是低光谱分辨率,要么仅提供一维视野。具有宽视场的高光谱分辨率成像器可能会产生千兆采样数据速率,这将导致实时数据处理出现问题。通过仅从场景的选定部分收集高光谱数据,我们将数据处理速率降低到可管理的水平。对于许多应用程序,只需要很小的视野,但是需要提示以了解情况。在我们的系统中,这是由宽视野的全色成像仪提供的,它在上述生物系统中起着与外围视觉类似的作用。我们的技术将所选区域成像到相干的光纤束上,然后将输入重新格式化为线阵列,从而构成色散高光谱成像仪的输入。计算机处理将分散的一维输出重新格式化为矩形图像,并应用校准例程以生成高光谱分辨率,小高光谱图像。这与高空间分辨率的全色图像结合在一起。将展示实验结果。

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