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A target detection multi-layer matched filter for color and hyperspectral cameras
Author(s): Tomoya Miyanishi; Bradley L. Preece; Joseph P. Reynolds
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Paper Abstract

In this article, a method for applying matched filters to a 3-dimentional hyperspectral data cube is discussed. In many applications, color visible cameras or hyperspectral cameras are used for target detection where the color or spectral optical properties of the imaged materials are partially known in advance. Therefore, the use of matched filtering with spectral data along with shape data is an effective method for detecting certain targets. Since many methods for 2D image filtering have been researched, we propose a multi-layer filter where ordinary spatially matched filters are used before the spectral filters. We discuss a way to layer the spectral filters for a 3D hyperspectral data cube, accompanied by a detectability metric for calculating the SNR of the filter. This method is appropriate for visible color cameras and hyperspectral cameras. We also demonstrate an analysis using the Night Vision Integrated Performance Model (NV-IPM) and a Monte Carlo simulation in order to confirm the effectiveness of the filtering in providing a higher output SNR and a lower false alarm rate.

Paper Details

Date Published: 23 May 2018
PDF: 18 pages
Proc. SPIE 10625, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIX, 1062510 (23 May 2018); doi: 10.1117/12.2306344
Show Author Affiliations
Tomoya Miyanishi, Acquisition, Technology & Logistics Agency (ATLA) (Japan)
Bradley L. Preece, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Joseph P. Reynolds, U.S. Army Night Vision & Electronic Sensors Directorate (United States)


Published in SPIE Proceedings Vol. 10625:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIX
Gerald C. Holst; Keith A. Krapels, Editor(s)

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