Imaging principle: Hyperspectral cameras have a different imaging principle than ordinary cameras. Ordinary cameras focus light reflected or transmitted by visible light through an optical
lens onto a light-sensitive element to form a color or black-and-white image. Hyperspectral cameras, on the other hand, use multi-channel spectral sensors that can simultaneously capture spectral data in hundreds of bands in the visible and infrared spectral range. This allows hyperspectral cameras to provide richer
spectral information and material identification.
Spectral information: Hyperspectral cameras and ordinary cameras differ in the spectral information they provide. Ordinary cameras provide three-channel color information, i.e., the intensity of red, green and blue colors. Hyperspectral cameras, on the other hand, can provide hundreds of bands of spectral data and can more
accurately identify the spectral characteristics of different substances. This makes hyperspectral cameras more accurate in substance identification, feature classification and environmental
monitoring.
Data Acquisition: There are also differences in data acquisition methods between hyperspectral cameras and ordinary cameras. Ordinary cameras usually use a single exposure to
acquire image data, which is suitable for instantaneous scene shooting. Hyperspectral cameras, on the other hand, usually use continuous scanning to acquire continuous spectral
data at a faster rate. This makes hyperspectral cameras suitable for real-time monitoring, change detection and continuous data acquisition needs.
Application areas: Hyperspectral cameras and ordinary cameras also differ in application areas. Ordinary cameras are mainly used for photography, video shooting and general image
acquisition needs, such as portrait photography, landscape shooting and advertising. While hyperspectral cameras are mainly used in remote sensing, agriculture, environmental monitoring,
medical diagnosis and cultural relics protection and other fields. The multi-spectral information and material identification capability of hyperspectral cameras enable them to provide more
detailed surface information and more accurate data analysis.
Price and complexity: Hyperspectral cameras are more expensive and complex compared to ordinary cameras due to their more complex optical systems and data processing requirements
. Hyperspectral cameras typically require more optics, spectral sensors, data processing algorithms, etc., resulting in higher costs. At the same time, the operation and data processing
of hyperspectral cameras are also more complex and require specialized knowledge and skills.
There are significant differences between hyperspectral cameras and ordinary cameras in terms of imaging principle, spectral information, data acquisition, application areas, as well as price
and complexity. Hyperspectral cameras play an important role in remote sensing, agriculture, environmental monitoring and other fields with their multispectral information and material
identification capabilities, while ordinary cameras are more suitable for general photography and image acquisition needs. The selection of a suitable camera should be based on compreh
ensive consideration of specific application needs and budget.
