Imaging in several wavelength bands. Differences in spectral reflectance can distinguish surface materials, including vegetation and water.
An image formed by dividing corresponding calibrated pixels in two spectral bands. If their signals have a common multiplicative factor, and , their ratio is and does not depend on . This explains suppression of some common illumination effects and enhancement of spectral contrasts. Additive atmospheric radiance and small denominators prevent exact cancellation and can amplify errors. Normalized difference vegetation index is a related normalized spectral contrast.
The normalized contrast of red and near-infrared reflectances. Large positive values indicate a vegetation-like spectrum, but soil, atmosphere, shadows and canopy saturation affect its interpretation.
A displayed image assigning measured bands to colour channels that differ from ordinary visual perception. Assigning near-infrared to red is a common way to highlight vegetation.
The steep increase of healthy green vegetation reflectance between red absorption and the high near-infrared scattering plateau, typically around 0.68–0.75 micrometres.
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Multispectral imaging is a technique that captures image data at specific frequency ranges across the electromagnetic spectrum. Unlike traditional imaging that typically uses only visible light, multispectral imaging collects data across multiple wavelengths, including ultraviolet, visible, and infrared light. The key features of multispectral imaging include: 1. **Multiple Wavelengths**: Multispectral cameras capture data from several discrete bands, usually ranging from 3 to 10 different wavelengths, though some systems may capture more.