Paper
23 October 2014 Airborne hyperspectral imaging in the visible-to-mid wave infrared spectral range by fusing three spectral sensors
Dainis Jakovels, Jevgenijs Filipovs, Gatis Erinš, Juris Taskovs
Author Affiliations +
Abstract
Airborne hyperspectral imaging is widely used for remote sensing of environment. The choice of spectral region usually depends on the availability and cost of the sensor. Visible-to-near infrared (400-1100 nm) spectral range corresponds to spectral sensitivity of relatively cheap Si detectors therefore it is the most commonly used. The implementation of shortwave infrared (1100-3000 nm) requires more expensive solutions, but can provide valuable information about the composition of the substance. Mid wave infrared (3000-8000 nm) is rarely used for civilian applications, but it provides information on the thermal emission of materials. The fusion of different sensors allows spectral analysis of a wider spectral range combining and improving already existing algorithms for the analysis of chemical content and classification. Here we introduce our Airborne Surveillance and Environmental Monitoring System (ARSENAL) that was developed by fusing seven sensors. The first test results from the fusion of three hyperspectral imaging sensors in the visible-to-mid wave infrared (365-5000 nm) are demonstrated. Principal component analysis (PCA) is applied to test correlation between principal components (PCs) and common vegetation indices.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dainis Jakovels, Jevgenijs Filipovs, Gatis Erinš, and Juris Taskovs "Airborne hyperspectral imaging in the visible-to-mid wave infrared spectral range by fusing three spectral sensors", Proc. SPIE 9245, Earth Resources and Environmental Remote Sensing/GIS Applications V, 92450P (23 October 2014); https://doi.org/10.1117/12.2067151
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Cited by 4 scholarly publications.
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KEYWORDS
Sensors

Infrared radiation

Vegetation

Infrared sensors

Infrared imaging

Hyperspectral imaging

Principal component analysis

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