Target detection from noise-reduced hyperspectral imagery using a spectral unmixing approach

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Authors
  1. Qian, S-E.
  2. Lévesque, J.
Corporate Authors
Defence R&D Canada - Valcartier, Valcartier QUE (CAN);Canadian Space Agency, St-Hubert Que (CAN)
Abstract
We assess the effectiveness of a previously proposed noise reduction technology for hyperspectral imagery to examine whether it can better serve remote sensing applications after noise reduction using the technology. Target detection from hyperspectral imagery using a spectral unmixing approach is selected as an example in the assessment. A hyperspectral datacube acquired using an airborne short-wave-infrared Full Spectrum Image II with man-made targets in the scene of the datacube is tested. Three criteria are proposed and used to evaluate the detectability of the targets derived from the datacube before and after noise reduction. The evaluation results show that the detectability of the targets is significantly improved after noise reduction using the technology. The targets not detected from the original datacube are detected with high confidence after noise reduction using the technology. A noise reduction technique that is based on a smoothing approach is also evaluated for the sake of comparison to the proposed noise reduction technology. It also improves the detectability of the targets, but is less effective than the proposed noise reduction technology.
Report Number
DRDC-VALCARTIER-SL-2009-098 — Scientific Literature
Date of publication
01 Feb 2009
Number of Pages
11
Reprinted from
Optical Engineering, vol 48(2), 2009, p 1-11
DSTKIM No
CA032743
CANDIS No
532010
Format(s):
Document Image stored on Optical Disk

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