A method for designing pixelated camouflage patterns for forest terrain backgrounds

Camouflage is a critical component of modern military operations, enabling objects to blend visually into their surroundings. Traditional disruptive patterns used widely from the 1970s to early 2000s are increasingly replaced by pixelated camouflage. This study proposes a design method for pixelated camouflage patterns tailored to forest terrain. Effectiveness is evaluated using Peak Signal-to-Noise Ratio (PSNR) and Histogram Intersection (HI), which assess visual and color similarity. Results show the designed patterns resemble forest backgrounds in color and texture, indicating practical potential.

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Publication Details

Journal
Journal of Military Science and Technology
Published
2025-10-02
DOI
https://doi.org/10.54939/1859-1043.j.mst.106.2025.121-128
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
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article

A method for designing pixelated camouflage patterns for forest terrain backgrounds

Đình Phương Thảo Nguyễn, Thanh Thi Nguyen
Journal of Military Science and Technology
Remote Sensing and LiDAR Applications
article

A method for designing pixelated camouflage patterns for forest terrain backgrounds

Đình Phương Thảo Nguyễn, Thanh Thi Nguyen
article en

Abstract

Camouflage is a critical component of modern military operations, enabling objects to blend visually into their surroundings. Traditional disruptive patterns used widely from the 1970s to early 2000s are increasingly replaced by pixelated camouflage. This study proposes a design method for pixelated camouflage patterns tailored to forest terrain. Effectiveness is evaluated using Peak Signal-to-Noise Ratio (PSNR) and Histogram Intersection (HI), which assess visual and color similarity. Results show the designed patterns resemble forest backgrounds in color and texture, indicating practical potential.

Journal of Military Science and TechnologyVol. 106
Academy of Military Medical Sciences (CN)
Openalex Percentile: Top 75%
Remote Sensing and LiDAR Applications
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