spectrumimaging

Spectrum imaging is an imaging modality that records spectral information for every location in an image. The resulting data form a cube with two spatial dimensions and one spectral dimension, enabling identification and characterization of materials by their spectral signatures, which reflect molecular composition, structure, and state. Spectrum imaging is commonly referred to as hyperspectral imaging when many narrow spectral bands are recorded, and as multispectral imaging when fewer, broader bands are used.

Acquisition methods include dispersive imaging spectrometers that route light to a detector to measure a full spectrum at each pixel, filter-based approaches such as tunable filters or filter wheels, and snapshot systems that capture all wavelengths in a single exposure. Instruments range from scientific imaging spectrometers used in remote sensing and laboratory analysis to specialized cameras for industrial inspection and biomedical research. Data are typically organized as a data cube, with two spatial axes and one spectral axis, spanning portions of the visible, near-infrared, shortwave infrared, and other ranges depending on the application.

Applications span remote sensing and earth observation, precision agriculture, mineralogy and material identification, food quality control, pharmaceutical manufacturing, medical imaging and pathology, and art conservation. In research and industry, spectrum imaging supports material discrimination, compositional analysis, and non-destructive testing.

Processing and analysis involve calibration (radiometric and geometric), noise reduction, and sometimes atmospheric correction for outdoor data. Analytical techniques include spectral unmixing to estimate material abundances, dimensionality reduction, feature extraction, and supervised or unsupervised classification, often aided by machine learning and spectral libraries. Challenges include large data volumes, high dimensionality, calibration and illumination variability, mixed pixels, and the complexity and cost of acquisition systems.