Multispectral Imaging vs Hyperspectral Imaging: Key Differences Explained
- Anvita Shrivastava
- 5 days ago
- 4 min read
Updated: 4 days ago
In the last ten years, the improvement of imaging technology has led to new ways for businesses to acquire imaging data that are significantly better than those attainable by the human eye. The two highest-quality imaging techniques currently in use—multispectral imaging (MSI) and hyperspectral imaging (HSI)—have completely changed how these types of imaging are used for agriculture, healthcare, industrial inspection, environmental monitoring, defense, remote sensing, and many other industrial markets.
The two different methods of imaging may appear to be similar; however, they are substantially different with respect to the amount of spectral resolution, data complexity, amount of processing, and types of applications. How to select which imaging system best meets your needs will depend on your application specifics, cost limitations, and level of precision needed.
What Does Multispectral Imaging Mean?
Multispectral imaging captures image data over a range of a few discrete bands of wavelengths (typically from 3 – 20) in selected locations of the visible and near-infrared (NIR) part of the spectrum for measuring particular wavelengths.
Rather than capturing image data for all wavelengths within the electromagnetic spectrum, MSI captures image data only for specific regions of the electromagnetic spectrum that are especially useful for a specific purpose.
Some Advantages of Multispectral Imaging
3 – 20 Bands of Wavelength Data Captured
Low Data Volume
Rapid Image Acquisition
Low Hardware and Storage Requirements
Cost Effective
Easy Data Processing
The use of multispectral imaging captures image data over fewer bands of wavelengths than, for example, hyperspectral imaging, thus providing an ideal combination of performance (results), speed (time to get those results), and affordability (cost of the technology that provides those results).
What is hyperspectral imaging?
Hyperspectral imaging (HSI) is a type of imaging that captures many, usually thousands of individual images, each with its own spectral characteristics. For most HSI systems, there are between 100 and 400 spectral bands of light captured.
An HSI image is composed of many light pixels, known as "hyperspectral pixels." Each pixel contains a spectral signature for a target material. This allows the system to identify materials and how they interact with light based on their unique reflectance or spectral features.
Using these characteristics to classify materials, it allows for much more accurate identification of materials, chemical analyses, and the detection of anomalies.
Key characteristics of hyperspectral imaging
The ability to capture hundreds of narrow bands
They provide continuous spectrals
They provide very high spectral resolution.
They generate a lot of data.
They will typically require a lot of computing power.
They provide very good material discrimination.
Hyperspectral imaging is commonly referred to as spectral fingerprinting because all materials have distinct ways of reflecting light from the entire electromagnetic spectrum.
Multispectral Imaging vs. Hyperspectral Imaging: Side-by-Side Comparison
Feature | Multispectral Imaging | Hyperspectral Imaging |
Number of Spectral Bands | 3–20 | 100–400+ |
Spectral Resolution | Moderate | Very High |
Band Width | Wider | Narrow |
Data Volume | Low | Very High |
Processing Speed | Faster | Slower |
Storage Requirements | Low | High |
Hardware Cost | Lower | Higher |
Computational Complexity | Moderate | High |
Material Identification | Good | Excellent |
Real-Time Capability | Better | Limited |
Multispectral Imaging Advantages
Low Cost
Multispectral Imaging Systems typically cost less than conventional imaging sensors, which makes them more cost-effective solutions in the commercial/industrial sectors.
High-Speed Data Processing
Due to the smaller size of multispectral datasets, they require significantly less computational power, which allows for the nearly instantaneous processing of the data.
Reduced Storage Requirements
The reduced size of the data collected from a multispectral imaging system reduces the cost of storing the data as well as making it easier to manage.
Easier Integration
Multispectral imaging systems are much easier to integrate into drones, production lines, satellites, and robotic systems.
Hyperspectral Imaging Advantages
Exceptional Material Identification
Hyperspectral Imaging can identify materials that look identical but are chemically different.
More Accurate Chemical Data
When using a hyperspectral imaging system, the spectral information collected can be used to provide accurate results regarding the chemical composition of all materials.
Higher Gold Sulfide Detection
Hyperspectral imaging has the ability to detect very small defects and/or differences in the presence of contaminants, moisture level, and/or the composition of a large area of gold.
Rich Data for AI Models
Hyperspectral imaging provides an abundance of spectral information that can be utilized for Machine Learning & Deep Learning Algorithms to train, validate, and optimize.
Multispectral Imaging Limitations
Spectra have limited resolution.
Fewer opportunities to distinguish between materials
Less accuracy for complex analyses
Misses fine spectral variances
Hyperspectral Imaging Limitations
Very costly to collect data
Large amounts of data
Long processing times
Great increase in the size of files needed for storage
More complicated to calibrate and analyse
Future Trends
The advancement of AI, Edge Computing, Sensor Miniaturization, and Cloud-based Analytics is reducing the cost of the technology and making both technologies more accessible.
Innovations that have recently emerged include the following:
AI-Enabled Spectral Analysis
Lightweight Hyperspectral Cameras for Drones
Real-Time Processing of Hyperspectral Data
Edge AI Imaging Systems
High-Speed Industrial Inspection of Hyperspectral Data
As hardware prices decrease and algorithms improve, we expect to see more widespread use of hyperspectral imaging across a variety of commercial industries.
Both multispectral imaging and hyperspectral imaging are powerful imaging technologies that enable organizations to process and evaluate objects outside the visible light spectrum. Although multispectral imaging provides speed, affordability, and operational efficiency, hyperspectral imaging enables users to access unprecedented levels of spectral detail, which allows for advanced material identification and scientific evaluations.
By understanding the differences between multispectral and hyperspectral imaging technologies, commercial companies, researchers, and engineers can select the appropriate imaging method for their applications. Choosing the right imaging technology can greatly improve decision-making, automation, and accuracy of inspections.
For more information or any questions regarding multispectral imaging and hyperspectral imaging, please don't hesitate to contact us at:
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USA (HQ): (720) 702–4849
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