
Proceedings Paper
Case-study analysis of apparent camouflage-pattern color using segment-weighted spectraFormat | Member Price | Non-Member Price |
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Paper Abstract
Advanced camouflage patterns, consisting of highly detailed camouflage patterning, require additional methodologies for color evaluation, which is with respect to realistic field conditions. A quantitative metric for evaluation of comouflage patterns, as viewed under realistic field conditions, is “apparent color,” which is the combination of all visible wavelengths (380-700 nm) of light reflected from large camouflage-pattern samples (≥1m2 ) for a given standoff distance (25-100 ft). Camouflage patterns lose resolution with increasing standoff distance, and eventually all colors within the pattern combine and thus appear monotone (the “apparent color” of the camouflage pattern). This paper presents a case-study analysis of apparent camouflage-pattern color using segment-weighted reflectance spectra for the purpose of evaluating apparent color of advanced camouflage patterns with respect to realistic field conditions. Simulation of apparent camouflage-pattern color using this methodology is based on decomposition of camouflage-pattern reflectance with respect to component segments of camouflage patterns.
Paper Details
Date Published: 14 May 2019
PDF: 8 pages
Proc. SPIE 10986, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV, 109861R (14 May 2019); doi: 10.1117/12.2513458
Published in SPIE Proceedings Vol. 10986:
Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV
Miguel Velez-Reyes; David W. Messinger, Editor(s)
PDF: 8 pages
Proc. SPIE 10986, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV, 109861R (14 May 2019); doi: 10.1117/12.2513458
Show Author Affiliations
S. Ramsey, U.S. Naval Research Lab. (United States)
T. Mayo, U.S. Naval Research Lab. (United States)
C. Howells, U.S. Army Reserve (United States)
T. Mayo, U.S. Naval Research Lab. (United States)
C. Howells, U.S. Army Reserve (United States)
A. Shabaev, Leidos, Inc. (United States)
S. G. Lambrakos, U.S. Naval Research Lab. (United States)
S. G. Lambrakos, U.S. Naval Research Lab. (United States)
Published in SPIE Proceedings Vol. 10986:
Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV
Miguel Velez-Reyes; David W. Messinger, Editor(s)
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