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NIR hyperspectral compressive imager based on a modified Fabry-Perot resonator

机译:基于改进的法布里 - 珀罗谐振器的NIR高光谱压缩成像器

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The acquisition of hyperspectral (HS) image datacubes with available 2D sensor arrays involves a time consuming scanning process. In the last decade, several compressive sensing (CS) techniques were proposed to reduce the HS acquisition time. In this paper, we present a method for near-infrared (NIR) HS imaging which relies on our rapid CS resonator spectroscopy technique. Within the framework of CS, and by using a modified Fabry-Perot resonator, a sequence of spectrally modulated images is used to recover NIR HS datacubes. Owing to the innovative CS design, we demonstrate the ability to reconstruct NIR HS images with hundreds of spectral bands from an order of magnitude fewer measurements, i.e. with a compression ratio of about 10:1. This high compression ratio, together with the high optical throughput of the system, facilitates fast acquisition of large HS datacubes.
机译:使用可用的2D传感器阵列的高光谱(HS)图像Datacubes的获取涉及耗时的扫描过程。 在过去的十年中,提出了几种压缩感测(CS)技术来减少HS采集时间。 在本文中,我们介绍了一种近红外(NIR)HS成像的方法,其依赖于我们的快速CS谐振器光谱技术。 在CS的框架内,并且通过使用改进的法布里 - 珀罗谐振器,使用一系列谱调制图像来恢复NIR HS Datacubes。 由于创新的CS设计,我们展示了从数百个幅度测量的数百个谱带重建NIR HS图像的能力,即压缩比为约10:1。 这种高压缩比与系统的高光吞吐量一起有助于快速获取大型HS Datacubes。

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