Modeling apparent camouflage patterns for visual evaluation

S. Ramsey; T. Mayo; C. Howells; A. Shabaev; S. G. Lambrakos

doi:10.1117/12.2300941

8 May 2018 Modeling apparent camouflage patterns for visual evaluation

S. Ramsey, T. Mayo, C. Howells, A. Shabaev, S. G. Lambrakos

Proceedings Volume 10644, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV; 1064428 (2018) https://doi.org/10.1117/12.2300941
Event: SPIE Defense + Security, 2018, Orlando, FL, United States

Abstract

Advanced camouflage patterns for military applications consist of highly detailed camouflage patterning and multiple tonal (blended) colors. The complexity of these camouflage patterns establishes a need for additional test methodologies for color and pattern evaluation. One metric for evaluation is apparent color, which is the combination of all visible wavelengths (380-700 nm) of light reflected from large (≥1m²) fabric sample sizes for a given standoff distance (25-100 ft). This follows in that camouflage patterns lose resolution with increasing standoff distance, and eventually all colors within the pattern appear monotone (the “apparent color” of the camouflage pattern). The concept of apparent color, however, is based on far-field and statistical characteristics of camouflage patterns. In contrast, the concept of apparent camouflage pattern is to be associated with intermediate distances between observer and target. Accordingly, quantitative metrics for camouflage-pattern viability based on apparent patterns should be different than those for apparent color, thus providing additional criteria for evaluation. This paper presents discussion and prototype simulations based on the concept of apparent camouflage pattern for model development relevant to evaluating camouflage fabrics.

Citation Download Citation

S. Ramsey, T. Mayo, C. Howells, A. Shabaev, and S. G. Lambrakos "Modeling apparent camouflage patterns for visual evaluation", Proc. SPIE 10644, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, 1064428 (8 May 2018); https://doi.org/10.1117/12.2300941

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