Research news on multispectral imaging

Multispectral imaging is an optical acquisition method that records scene radiance or reflectance in multiple discrete spectral bands, typically spanning the visible, near-infrared, and sometimes shortwave infrared regions. Using bandpass filters, tunable filters, or sensor arrays with spectrally selective elements, it generates co-registered images where each band captures wavelength-dependent material properties. Quantitative analysis of these bands enables spectral feature extraction, classification, and segmentation based on differences in absorption, scattering, or fluorescence. In research, multispectral imaging is applied to non-destructive assessment, tissue characterization, remote sensing, and cultural heritage analysis, often serving as a lower-complexity, higher-throughput alternative to full hyperspectral imaging.

Mapping wildfire risk across the US, day by day

Wildfires can spread fastest when they tear through areas of dry vegetation. In contrast, vegetation that contains a lot of moisture can slow a wildfire's advance and give firefighting crews precious time to contain the blaze.

The 20th data release of the Sloan Digital Sky Survey

The Sloan Digital Sky Survey (SDSS), the largest multispectral imaging and spectroscopic redshift survey of the cosmos, has released its 20th data release (DR 20). It is also the third release of the survey's fifth phase ...

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