Paper
12 August 2004 A general spectral target signature transform
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Abstract
This report examines a series of multispectral or hyperspectral image data cubes collected of a given scene at different times. The diagonal, whitening/dewhitening, and target CV (Covariance) transformations use collected image data of spatially overlapping regions from data sets collected at different times to evolve target spectral signatures. The previously studied registration-free transformations are described using a single general equation and form a subset of a larger family of accurate transforms. The diagonal, whitening/dewhitening, and target CV transformations are characterized by a parameter n having n=0,1, 2 respectively. The transformed target signatures, used in matched filter searches, are tested on images taken from two data collects that use different sensors, targets, and backgrounds. Transforms with n between 0 and 2 yield the largest Target to Clutter Ratio (TCR) and remain relatively constant for 0
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rulon R. Mayer, Frank Bucholtz, Dean A. Scribner, and Melvin R. Kruer "A general spectral target signature transform", Proc. SPIE 5425, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X, (12 August 2004); https://doi.org/10.1117/12.548758
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KEYWORDS
Sensors

Target detection

Long wavelength infrared

Detection and tracking algorithms

Phase modulation

Image filtering

Image sensors

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