Hyperspectral imaging technology integrates imaging and spectral analysis capabilities, breaking through the limitations of traditional optical imaging. By capturing the light signals of target objects within continuous narrow bands, this technology can simultaneously analyze the spatial features and fine spectral information of objects. Each pixel can not only present position information but also contains data from dozens to hundreds of spectral channels ranging from visible light to near - infrared and even wider bands, with a spectral resolution reaching the 10 - nm level. This unique technological advantage makes it a core tool in fields such as environmental monitoring, agricultural management, and medical diagnosis.

 

I. Technical Principle and Core Components

The hyperspectral imaging system realizes data collection through the following core steps:

1. Light Source and Illumination: Standardized light sources or natural light are used to cover the object to be measured, stimulating its reflection, absorption, or transmission characteristics. For example, the reflectance of plant leaves to near - infrared light is significantly different between healthy and diseased states.

2. Spectral Separation: Gratings, prisms, or filter arrays are used to decompose the composite light into continuous narrow bands. For example, each 10 - nm band within the 400 - 1000 - nm range corresponds to the response characteristics of different components. This process can identify the unique "spectral fingerprint" of substances, such as the absorption characteristics of chlorophyll in specific bands.

3. Signal Detection: Detector arrays (such as silicon - based or InGaAs sensors) capture the decomposed spectral signals, generating a three - dimensional data cube that includes spatial and spectral dimensions. Micro - hyperspectral systems can also be combined with optical microscopes to analyze biological sections or the microscopic structure of materials at the micrometer scale.

 

II. Core Advantages and Application Scenarios

1. Precision Monitoring in Agriculture

Hyperspectral imaging enables "non - destructive diagnosis" in agriculture. By using equipment carried by drones or satellites, spectral data of farmland can be obtained over a large area:

 - Pest and disease early warning: Diseased plants change the reflectance of red light and near - infrared light, resulting in a shift of the "red edge" in the spectrum. Domestic research shows that the accuracy of this method in identifying wheat rust reaches 98%, significantly better than traditional manual inspections.

 - Soil composition analysis: The water content, nitrogen, phosphorus, and potassium content of soil can be inverted through spectral characteristics to guide precision fertilization.

2. Environmental and Resource Exploration

 - Mineral identification: Different minerals show characteristic absorption peaks in the short - wave infrared band, which can assist geological exploration.

 - Water quality monitoring: The concentration of algae and pollutants can be quantified through the reflection spectrum of water bodies. For example, cyanobacteria have strong reflection characteristics at the 620 - nm band.

3. Medicine and Life Sciences

Micro - hyperspectral systems can simultaneously acquire data on cell morphology and biochemical components:

 - Pathological analysis: The spectral differences between cancer cells and normal cells can be used for early diagnosis.

 - Drug R & D: Observe the absorption changes of drug molecules in specific bands to track their distribution in biological tissues.

 

III. Technological Development Prospects

With the improvement of detector accuracy and the optimization of data processing algorithms, hyperspectral imaging is developing towards higher resolution and wider spectral ranges. For example, some systems have expanded the spectral coverage to 250 - 15000 nm and combined with machine - learning models to achieve automatic substance classification. Against the background of carbon neutrality, this technology can also be used for carbon emission monitoring and ecological restoration evaluation to promote sustainable development.

Through the in - depth integration of spatial and spectral information, hyperspectral imaging technology is reshaping the practice paradigms of industrial inspection, scientific research, and environmental protection, and has become a key infrastructure for refined analysis and intelligent decision - making.