Multispectral & Hyperspectral Imaging
See What Conventional Cameras Cannot
Colour and intensity alone cannot reveal every property of an object.
Multispectral and hyperspectral imaging extend machine vision beyond conventional RGB by analysing how materials interact with light across defined wavelength ranges. Instead of simply capturing colour, spectral imaging can reveal material differences, chemical properties and defects that may otherwise remain invisible.
From Images to Material Information
Material Classification
Differentiate objects based on their spectral response without physical contact.
Invisible Defect Detection
Identify properties and defects that conventional visible imaging cannot reveal.
Composition & Quality
Use spectral information to investigate characteristics such as material composition, moisture or fat content.
Plant Health
Detect spectral changes associated with plant condition, disease and stress.
Multispectral or Hyperspectral?
Multispectral Imaging
Captures selected wavelength bands chosen for known characteristics or differences.
It can be highly effective when the relevant spectral information is already understood and only specific wavelength ranges need to be monitored.
Hyperspectral Imaging
Captures a much larger number of contiguous spectral bands, providing detailed spectral information for every pixel.
It is particularly valuable when material differences are complex, unknown or require deeper spectral analysis.
The current portfolio input describes multispectral configurations using one to four sensors and hyperspectral systems with up to 407 spectral bands.
Find the Right Spectral Imaging Technology
The right spectral camera depends on what you need to distinguish.
Wavelength range, spectral resolution, spatial resolution, acquisition method, object speed and illumination all influence the imaging approach.
Laser 2000 provides access to a broad range of spectral imaging technologies, from multispectral systems to hyperspectral imaging extending from near-UV and visible wavelengths into SWIR and eSWIR.
Not sure which wavelengths reveal the information you need? Our experts can help evaluate your application and, where appropriate, feasibility testing with sample materials.
Typical Applications
Recycling & Sorting
Differentiate plastics, fibres, waste streams and other materials based on spectral characteristics.
Food Quality
Inspect products and identify material or quality differences beyond conventional colour imaging.
Agriculture & Plant Health
Monitor vegetation, plant condition and biological changes.
Pharmaceutical Quality Control
Analyse products and materials using non-contact spectral information.
Mining & Geology
Identify and differentiate minerals and geological materials.
Remote Sensing & Research
Acquire spatial and spectral information for environmental, agricultural and scientific analysis.
Why Laser 2000
Explore Related Camera Technologies
High-Speed Cameras
Capture fast-moving objects and dynamic processes without losing critical information.
High-Resolution Cameras
Detect small features and defects while maintaining a large field of view.
Knowledge Centre
Guides, insights and resources across photonics applications and technologies.
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Frequently Asked Questions
Do I need multispectral or hyperspectral imaging?
Multispectral imaging is often sufficient when the relevant wavelengths are already known. Hyperspectral imaging is better suited when material differences are complex or not yet fully understood. Our experts can help evaluate which approach fits your application.
Which wavelength ranges are available?
Our portfolio covers near-UV and visible wavelengths through to SWIR and eSWIR, depending on the specific system and application.
Can I test spectral imaging on my own materials before committing?
Yes. Where appropriate, we can support feasibility testing with sample materials to help evaluate whether spectral imaging can solve your application.
Can Spectral Imaging Solve Your Application?
If you’re unsure which spectral range or imaging approach is required, start with the material or property you need to distinguish.