8 May 2018 A computational approach to hyperspectral imaging for long-range target identification
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For long range targeting, the limited focal length and aperture size associated with compact imaging sensors for airborne operation limit both the spatial resolution and the image brightness. This presents a serious challenge to the identification and tracking of targets. Algorithms that derive target shape and track movement through a scene require a resolved image and use pixel contrast to discriminate the target image from the background. This is of limited use when practical deployment demands the use of compact imaging systems with necessarily limited spatial resolution.

To address this we consider a 2D mosaic filters sampling scheme to acquire an incomplete multispectral data cube on a single frame readout from a focal plane array. Specifically, the sparse data cube contains 4 x 4 spatial cells and 16 wavebands with each waveband sampled once per cell; this corresponds to a 1/16 undersampling of the data cube. Complete multispectral images are then computed using compressed sensing protocols.

Results obtained using hyperspectral datasets from AVIRIS and Stanford University (SCIEN) are presented to demonstrate image reconstruction using 16 wavebands in the visible and near infrared. The function of the mosaic filter is mimicked by sampling the full dataset according to the design of a theoretical mosaic filter. This allows us to investigate different sampling strategies and, in particular, make a direct comparison between random and regular sampling. Our results show that the reconstruction error is strongly dependent on both the colour content and the sampling strategy in the test images, and that very good reconstruction can be achieved approaching the spatial resolution of the original image. Our results can be applied to both the MWIR and LWIR where the lower spectral resolution means that a smaller number of wavebands is likely to be sufficient for identification and tracking. The concept can also be extended to polarimetric imaging with a suitable polarimetric filter mask to provide a dual-mode polarimetric-multispectral imaging capability. This paper presents an overview of the technical approach and the general conclusions.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Simon Vary, Simon Vary, Andrew Thompson, Andrew Thompson, David Humphreys, David Humphreys, Jared Tanner, Jared Tanner, Robert A. Lamb, Robert A. Lamb, } "A computational approach to hyperspectral imaging for long-range target identification", Proc. SPIE 10644, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, 106440Q (8 May 2018); doi: 10.1117/12.2305306; https://doi.org/10.1117/12.2305306

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