LiCHI – Liquid Crystal Hyperspectral Imager for simultaneous multispectral imaging in aeronomy

In this paper, we present a technique for dimensionality reduction in hyperspectral imaging during the data collection process. A four-channel hyperspectral imager using liquid crystal Fabry-Perot etalons has been built and used to verify this method for four applications: auroral imaging, plant study, landscape classification, and anomaly detection. This imager is capable of making measurements simultaneously in four wavelength ranges while being tunable within those ranges, and thus can be used to measure narrow contiguous bands in four spectral domains. In this paper, we describe the design, concept of operation, and deployment of this instrument. The results from preliminary testing of this instrument are discussed and are promising and demonstrate this instrument as a good candidate for hyperspectral imaging.

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Multichannel tunable imager architecture for hyperspectral imaging in relevant spectral domains

Goenka

Semeter

Noto

et al. 2016

Appl. Opt.

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ASI aurora search: an attempt of intelligent image processing for circular fisheye lens

et al. 2018

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The circular fisheye lens exhibits an approximately 180° angular field-of-view (FOV), which is much larger than that of an ordinary lens. Thus, images captured with a circular fisheye lens are distributed non-uniformly with spherical deformation. Along with the fast development of deep neural networks for normal images, how to apply it to achieve intelligent image processing for a circular fisheye lens is a new task of significant importance. In this paper, we take the aurora images captured with all-sky-imagers (ASI) as a typical example. By analyzing the imaging principle of ASI and the magnetic characteristics of the aurora, a deformed region division (DRD) scheme is proposed to replace the region proposals network (RPN) in the advanced mask regional convolutional neural network (Mask R-CNN) framework. Thus, each image can be regarded as a "bag" of deformed regions represented with CNN features. After clustering all CNN features to generate a vocabulary, each deformed region is quantified to its nearest center for indexing. On the stage of an online search, a similarity score is computed by measuring the distances between regions in the query image and all regions in the data set, and the image with the highest value is outputted as the top rank search result. Experimental results show that the proposed method greatly improves the search accuracy and efficiency, demonstrating that it is a valuable attempt of intelligent image processing for circular fisheye lenses.

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LiCHI – Liquid Crystal Hyperspectral Imager for simultaneous multispectral imaging in aeronomy

Cited by 2 publications

References 8 publications

Multichannel tunable imager architecture for hyperspectral imaging in relevant spectral domains

Multichannel tunable imager architecture for hyperspectral imaging in relevant spectral domains

ASI aurora search: an attempt of intelligent image processing for circular fisheye lens

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