How to Choose the Right Hyperspectral Camera

Ordinary RGB cameras can only capture images in red, green, and blue bands, whereas hyperspectral cameras can acquire spectral information in hundreds of continuous narrow bands. This allows them to obtain both a two-dimensional spatial image and a one-dimensional spectral feature curve of the target, enabling nondestructive material identification, quantitative analysis of components, and detection of tiny defects based on the material’s unique 'spectral fingerprint.' Currently, hyperspectral imaging devices are widely used in many fields, including industrial intelligence inspection, precision agriculture research, UAV remote sensing, laboratory material studies, and trace evidence detection.

The market for hyperspectral cameras is very diverse, with huge differences in spectral ranges, imaging architectures, and hardware specifications. Many buyers only compare specs on paper when choosing, ignoring whether the device matches their project scenarios, which often leads to low equipment utilization and project difficulties. This article presents a practical selection approach to help avoid purchasing traps and find hyperspectral imaging devices that meet your needs while offering good value for money.

I. Clarify the application scenario and define basic requirements

Selection principle: There is no universal hyperspectral camera that fits all situations; the optimal choice is the one that matches your actual usage scenario. First, outline three core aspects: the usage environment, the objects being inspected, and the equipment mounting format.

1.1 Main application scenarios and selection directions

Industrial production line inspection: Suitable for plastic material classification, internal food mold detection, textile color variation checks, film defect recognition, and print quality control. Prefer using push-broom line-scan hyperspectral cameras that support continuous scanning, match conveyor belt speeds, and pay attention to imaging frame rate and long-term operational stability.

Precision agriculture and field sampling: For nondestructive measurement of fruit and vegetable sugar content, early warning of crop pests and diseases, soil nutrient surveys, and vegetation growth analysis. Visible to near-infrared band models are recommended, with options for either fixed detection setups or lightweight portable hyperspectral cameras.

UAV-mounted remote sensing: For water environment monitoring, forestry surveys, large-scale farmland mapping, and ecological investigations. Key selection criteria: lightweight body, low power consumption, compact size, balancing spatial resolution and UAV flight endurance.

Laboratory research and analysis: For biological slice microscopy, new material spectral experiments, cultural relic component analysis, and chemical sample qualitative studies. Focus on spectral resolution, signal-to-noise ratio, and stray light suppression, and prioritize models compatible with third-party data analysis software.

Special trace detection: For forensic trace identification, document examination, and concealed trace screening, usually requiring a closed uniform lighting system. High sensitivity to weak spectral signals and imaging stability are crucial.

1.2 Differentiating Device Mounting Methods

- Desktop Fixed Installation: For offline sample testing in labs, with fewer restrictions on device size;

- Production Line Fixed Position: For industrial automation scenarios, installation space and protective conditions need to be confirmed in advance;

- Drone-Mounted: Strict control over total weight and power consumption;

- Handheld Portable Device: For outdoor mobile sampling, it's best to choose models that support independent power supply and built-in touch operation.

II. Core Parameter Guide – Avoid Misleading Specs

2.1 Spectral Range (Primary Selection Criterion)

Different substances have spectral absorption peaks in specific wavelength ranges, so there’s no need to blindly pursue extremely wide spectral coverage. Common industry wavelength divisions:

1. 400–700nm (Visible Light Range): Surface color difference detection, appearance defect screening;

2. 400–1000nm (Visible - Near Infrared, VNIR): Most versatile, preferred for agriculture monitoring, food testing, and routine scientific research;

3. 900–1700nm (Short-Wave Infrared, SWIR): Moisture detection, organic matter identification, polymer sorting, internal quality analysis of agricultural products;

4. 900–2500nm (Long & Short-Wave Infrared): Mineral identification, in-depth analysis of advanced materials, higher budget requirements.

Tip: If the focus is only on fruit and vegetable quality detection, there’s no need to purchase a full-range device up to 2500nm. Keep costs reasonable. The FigSpec FS-1X series has modular multi-band models offering 400–700nm, 400–1000nm, and 900–1700nm versions, so you can match the wavelength plan according to the spectral characteristics of the material.

2.2 Spectral Resolution

Measured in nm; the smaller the number, the better the ability to detect fine spectral differences.

- ≤2.5nm: University research, precise component identification, mineral analysis;

- 3–10nm: Industrial online sorting, routine agricultural monitoring (most commercial applications);

- >10nm: Large-scale rapid remote sensing surveys.

2.3 Spatial Resolution & Imaging Speed

Spatial resolution determines the smallest defect the device can identify, influenced by detector pixel specs, lens focal length, and working distance. Projects for tiny defect detection require higher pixel specs; large-area remote sensing can have more relaxed requirements. Imaging speed (line scanning frequency/frame rate) directly affects operational efficiency: static sample testing doesn’t need high speed; high-speed conveyor or dynamic target monitoring projects must prioritize scanning rate.

2.4 Signal-to-Noise Ratio (SNR) and Dynamic Range

The signal-to-noise ratio represents the camera's ability to capture weak spectral signals. The higher the value, the more stable the data collection for weakly reflective samples. When testing samples with low reflectivity or under limited lighting conditions, the key parameter to compare is the SNR.

III. Comparison of Three Mainstream Imaging Methods: Push-broom | Snapshot | Area-array Staring

Commercial hyperspectral cameras on the market mainly fall into three categories, each suited to different scenarios:

Push-broom (Line Scan)

Captures a full row of spectral information at a time and relies on relative movement between the camera and the sample to complete imaging of the entire area.

✅ Advantages: Excellent spectral resolution, high data integrity, supports long-term continuous operation;

✅ Suitable Scenarios: Industrial assembly lines, drone remote sensing, large-area sample scanning.

The FigSpec FS-1X series line-scan hyperspectral cameras use a mature push-broom optical architecture, with excellent stray light control and outstanding stability for long continuous imaging.

Snapshot Hyperspectral Camera

Acquires a complete 3D spectral image in a single exposure without requiring relative movement between the device and the sample;

✅ Advantages: Fast capture speed, suitable for imaging dynamic objects;

❌ Drawback: The number of spectral channels is usually fewer than line-scan models;

✅ Suitable Scenarios: Biological dynamic observation, high-speed instant sample collection.

Area-array Staring

More suitable for offline scanning of small static samples, widely used in basic laboratory testing.

IV. Often Overlooked Key Points: Software Ecosystem, Supporting Hardware, and Technical Services

Many buyers focus only on hardware specifications and neglect the supporting system, causing the equipment to be difficult to use once delivered.

Acquisition and Analysis Software

Check whether the manufacturer's software supports real-time spectral preview, reflectance correction, radiometric calibration, and spectral classification modeling; also confirm the data export formats and whether they can interface with mainstream third-party analysis tools like ENVI, MATLAB, and Python.

FigSpec's full range of hyperspectral cameras comes with dedicated acquisition and analysis software, built-in complete spectral preprocessing toolkits, and an open SDK interface, making it easy for enterprises to develop secondary applications and quickly integrate with automated production line control systems.

Lenses, Light Sources, and Other Accessories

Hyperspectral imaging quality heavily depends on the lighting system. During procurement, ensure the supplier can provide complete lighting solutions and lenses with various focal lengths, reducing additional purchase and tuning costs later.

Technical Support and Regular Calibration Services

Hyperspectral equipment requires periodic spectral calibration. Prioritize suppliers who can continuously provide sample testing, on-site debugging, and application solution development. Many manufacturers only sell hardware and lack application engineers to assist with spectral modeling, which can significantly extend the project implementation cycle.

V. Scenario-Based Camera Selection Reference List

✅ Industrial Online Sorting (Plastic, Food, Textile) Recommended: Push-broom line scan cameras | Preferred bands: 400–1000nm / 900–1700nm | Spectral resolution: 6–10nm | High scanning speed Reference models: FigSpec FS-13 series, high-pixel specifications, compatible with wide conveyor belts for continuous online inspection

✅ Precision Agriculture, Field Ground Sampling Recommended: Portable push-broom cameras, VNIR 400–1000nm | Spectral resolution: 2.5–6nm Reference models: FigSpec-IQ portable hyperspectral camera, lightweight body, supports independent outdoor power, touchscreen for real-time image and spectral curve viewing on-site

✅ UAV Remote Sensing Monitoring Recommended: Lightweight line scan cameras | Strictly control overall weight, low power design Reference models: FS60-C airborne hyperspectral imaging device, compatible with mainstream industrial drone mounting solutions

✅ Universities and Research Labs Recommended: High hyperspectral resolution cameras, support microscope mount extensions Reference models: FigSpec FS-10 series, can be paired with microscope components to build a microscopic hyperspectral system, suitable for spectral research at the biological or material micro-level

VI. Common Procurement Pitfall Avoidance

Pitfall 1: The wider the spectral band, the better Wider band devices cost more, and data storage and computation pressure increase later. Selecting bands based on the characteristic absorption peaks of the measured material is the most efficient approach.

Pitfall 2: Higher spec sheet parameters mean better real performance Optical structure design, stray light suppression, and detector calibration directly determine real imaging quality; promotional parameters are for reference only. If possible, prioritize actual sample testing for comparison.

Pitfall 3: Purchasing only the camera body and ignoring the full system Lens, uniform light source, calibration whiteboard, and analysis software are all essential; buying parts separately can easily lead to compatibility issues.

Pitfall 4: Ignoring secondary development support In automated production line projects, SDK interfaces and technical development support determine whether full automated intelligent inspection can be realized.

VII. Conclusion

Choosing the right hyperspectral camera follows a clear process: clarify application scenarios → confirm mounting form → match spectral bands → balance resolution and imaging speed → evaluate supporting software and technical service capabilities. Hyperspectral imaging is an integrated hardware-software solution; hardware parameters are just the foundation.

Complete supporting solutions and ongoing technical support directly determine project success. If you’re unsure which model fits, you can send samples for hyperspectral imaging tests and get precise selection suggestions based on actual spectral curves. The FigSpec hyperspectral series covers industrial line-scan, outdoor portable, UAV-mounted, and laboratory desktop solutions, and engineers can provide customized model selection and imaging test services for your samples.

FAQ:

Q1: What's the difference between a hyperspectral camera and a multispectral camera?

A: A multispectral camera only has a few discrete bands; a hyperspectral camera has hundreds of continuous narrow bands, allowing it to generate a complete continuous spectral curve for more accurate material identification.

Q2: Can a portable hyperspectral camera be used for field monitoring of farmland?

A: Absolutely. The lightweight FigSpec-IQ model supports battery-powered operation without needing an external power source, so it can be used directly for field sampling and soil surveys.

Q3: Can a hyperspectral camera be integrated into an automated production line?

A: Push-scan line-scan models are naturally suited for assembly line scenarios. They have open SDK interfaces and can work with vision control systems to achieve real-time online inspection and automatic sorting.

Q4: Does the camera need regular spectral calibration after purchase?

A: It's recommended to carry out regular radiometric and reflectance calibration. Reputable suppliers provide calibration tools and complete guidance on the calibration process.