A hyperspectral camera is an advanced imaging device capable of capturing detailed spectral information from objects or scenes, recording data across multiple wavelengths of light beyond what the human eye can see. Unlike conventional cameras that capture images in three primary colors—red, green, and blue—hyperspectral cameras can record hundreds or even thousands of wavelengths, providing a continuous spectrum for each pixel in the image. This rich spectral information allows for the precise identification of materials, analysis of chemical compositions, and detection of processes that are invisible to standard cameras. Used extensively in fields like remote sensing, agriculture, environmental monitoring, and medical diagnostics, hyperspectral cameras offer a powerful tool for detailed spectral analysis, enabling applications that range from monitoring crop health to detecting cancerous tissues.
Humanoid robot
As the "high-precision eyes" of robots, hyperspectral vision mainly includes imaging and analysis, from traditional imaging to multispectral imaging, from computational intelligence to cognitive intelligence, its development plays an important role in the control of robots.
Autonomous driving
Environmental perception is one of the important tasks in autonomous driving. In dark environments, it is hard for traditional cameras to capture images, radar and LiDAR have the same problems
Hyperspectral imaging sensor can effectively solve the problem, greatly improving the perception ability of the autonomous driving system in different environment.
Users can recognize, diagnose, and prewarn of skin surface inflammation, skin diseases, jaundice, vitiligo and cancer, through self-service photography, to achieve skin health management.
Through hyperspectral imaging microscopy and AI algorithm, fast, accurate, and safe intelligent diagnosis of pathological properties of tumor tissue slices is achievable.
- Freshness detection
- Detection of fat, moisture and protein content
- Quality classification
- Additives exceeding the standard for rapid screening
- Freshness and mold detection
- Sugar and moisture content detection
- Quality classification
- Rapid screening of pesticide residues exceeding standards
Monitoring of plant growth, pests and diseases risk
Accurate identification of seedling sprouts and tillers
Phenotypic analysis of frost resistance in tea seedlings
Tracking and prediction of grape ripeness
Based on micro hyperspectral on-site monitoring technology, it can effectively solve the industrial manufacturing status tracking and environmental governance monitoring, also, meeting the requirements on cost, accuracy, real-time performance and stability.
Meat Freshness
It can achieve contactless detection of diverse parameters such as freshness, fat, protein, calories, water content, pH value, as well as comprehensive analysis of meat quality.
Biometric Recognition
In biometric recognition, the spectral information feature of hyperspectral technology can effectively analyze skin composition improving the accuracy of biometric recognition.
Smart Agriculture
Hyperspectral imaging can be applied in fruit detection, monitoring and classification of crop, disaster monitoring, and yield estimation.
Skin Detection
Hyperspectral skin detection can achieve more accurate and than ordinary and multispectral image skin detection, it can be applied in cosmetics, scalp quality, skin diseases and others.
Full spectrum coverage empowers applications in different industries
| Parameter | Imaging modatites | Sensor | Field of Views(°) | Detect range(mm) | Spectral range(nm) | FWHM(nm) | Dynamic range(bit) |
|---|---|---|---|---|---|---|---|
| Performance |
MEMS wavelength scanning |
CMOS | 55 | 100 ~ ∞ | 400~900 (Optional) | 20 ~ 40 | 10 |
| Parameter | Spectral channels | Resolution(pixel) | Compatible OS | Power supply | Interface | Weight(g) | Dimensions (mm) |
|---|---|---|---|---|---|---|---|
| Performance | 1~255 optional | 1280*1024 | Windows/Linux/Android | ＜250mw | MIPI | 30 27 | 20x20x12 9.5x9.5x6.2 |
| Parameter | Imaging modatites | Sensor | Field of Views(°) | Detect range(mm) | Spectral range(nm) | FWHM(nm) | Dynamic range(bit) |
|---|---|---|---|---|---|---|---|
| Performance |
MEMS wavelength scanning |
CMOS | 55 | 100 ~ ∞ | 400~900 (Optional) | 15 ~ 30 | 10 |
| Parameter | Spectral channels | Resolution(pixel) | Compatible OS | Power supply | Interface | Weight(g) | Dimensions (mm) |
|---|---|---|---|---|---|---|---|
| Performance | 1~255 optional | 1280*1024 | Windows/Linux/Android | ＜250mw | MIPI | 30 | 20x20x12 |
| Parameter | Imaging modatites | Sensor | Field of Views(°) | Detect range(mm) | Spectral range(nm) | FWHM(nm) | Dynamic range(bit) |
|---|---|---|---|---|---|---|---|
| Performance |
MEMS wavelength scanning |
CMOS | 55 | 100 ~ ∞ | 400~900 (Optional) | 15 ~ 30 | 10 |
| Parameter | Spectral channels | Resolution(pixel) | Compatible OS | Power supply | Interface | Weight(g) | Dimensions (mm) |
|---|---|---|---|---|---|---|---|
| Performance | 1~255 optional | 1280*1024 | Windows/Linux/Android | 5V/3W | USB2.0, WIFI (2.4G/5G optional) | 235 | 112*56*34 |
