Hyperspectral vs Multispectral Imaging: Understanding the Difference and Choosing the Right Technology for Mobile Devices
Spectral imaging is changing how industries capture and analyze light across different wavelengths. It enables systems to identify materials, detect subtle color variations, and obtain accurate spectral data for diverse applications, from scientific research and remote sensing to quality control, skin care, medical imaging, and smartphones. These technologies deliver deeper insights than traditional RGB color imaging while continuing to evolve toward more compact and integrated designs.
Among the most common approaches are multispectral and hyperspectral imaging. Both provide advanced spectral information but differ in resolution, data complexity, and ease of integration into mobile and embedded devices.
This article explains the multispectral hyperspectral distinction and why multispectral imaging offers a practical and scalable solution for high-volume, embedded, and snapshot imaging applications.
Understanding Hyperspectral Imaging (HSI)
Hyperspectral imaging (HSI) captures hundreds of narrow and contiguous wavelength bands across a broad spectral range. Typical HSI systems measure 100–300+ bands with narrow bandwidths (≈ 5–20 nm), allowing for detailed spectral analysis. This provides extremely high spectral resolution but leads to longer measurement times and much larger data volumes.
HSI systems rely on scanning-based technologies such as pushbroom scanners, tunable filters, or whiskbroom sensors, which sequentially scan a scene or capture narrow spectral ranges one at a time. These architectures are not compatible with snapshot operation and result in larger, slower, more complex, and more expensive imaging systems, where real-time processing becomes highly challenging.
Hyperspectral imaging is mainly used in scientific research, remote sensing, mineral and material analysis, biomedical studies, and industrial inspection, where achieving the highest accuracy is more important than portability, and fine spectral discrimination is essential.
Understanding Multispectral Imaging (MSI)
Multispectral imaging (MSI) captures a smaller number of carefully selected wavelength bands, each representing a broader portion of the spectrum. MSI cameras offer a balance between detail and practicality by providing higher spectral resolution than standard RGB cameras while still allowing convenient snapshot-style captures.
While early MSI systems often used filter wheel mechanisms, the development of chip-scale filter technologies, such as organic color filters or interference filters deposited on CMOS sensors, has made it possible to achieve snapshot multispectral imaging, enabling compact, reliable, power-efficient, and cost-efficient systems with lightweight datasets that can be processed in real time.
The scalability of multispectral imaging makes it suitable for high-volume production and consumer markets, including smartphones, consumer electronics, wearables, medical and skin care diagnostics, robotics, and portable inspection tools.
Hyperspectral vs Multispectral: A Side-by-Side Comparison
To further illustrate the differences between multispectral and hyperspectral imaging, we provide both a conceptual diagram (Figure 1) and a comparison chart (Table 1) in this section. Together, they demonstrate how these imaging approaches differ in the number of spectral bands, data complexity, and suitability for various applications.
Figure 1 shows how spectral imaging technologies differ in the number and continuity of wavelength bands they capture. Traditional RGB captures three broad color bands, MSI uses a limited number of discrete bands for efficient spectral analysis, and HSI records hundreds of narrow, continuous bands for maximum details.
| Parameter | Multispectral Imaging (MSI) | Hyperspectral Imaging (HSI) |
| Number of Bands | 6 – 30 | 100 – 300 + |
| Band Width | Broad (≈ 20–50 nm) | Narrow (≈ 5–20 nm) |
| Spectral Resolution | High | Very high |
| Spatial Resolution | Higher | Lower |
| Data Size | Low – moderate | Very large |
| Processing Load | Light; real-time capable | Heavy; requires High-Performance Computing |
| Integration | Compact, mobile-ready | Bulky; lab/satellite setups |
| Cost & Maintenance | Affordable, low power | Expensive, calibration-intensive |
| Applications | Embedded, mobile, robotics, and portable devices | Research and industrial analysis |
Table 1: Comparison of Key Parameters Between Multispectral and Hyperspectral Imaging
Which One Is Right for Your Application?
Both hyperspectral and multispectral imaging deliver valuable insights depending on the use case.
Hyperspectral imaging is best for scientific research, remote sensing, and industrial inspection, where fine material differentiation is essential and data volume is manageable. Multispectral imaging, on the other hand, excels when devices need to be compact, fast, and scalable, such as in smartphones, consumer electronics, robotics, drones, or portable inspection tools.
MSI’s snapshot imaging capability, capturing multiple bands simultaneously without scanning, enables true real-time performance in compact systems. This makes it the preferred technology for mobile and embedded devices.
Ultimately, choosing between HSI and MSI depends on your application requirements, performance specifications, and budget. Before selecting a technology, assess the level of spectral detail, spatial resolution, data volume, processing speed, integration constraints, and available budget your system demands. Conducting this evaluation will help identify which imaging approach best aligns with your technical goals, operational needs, and cost considerations.
Spectricity’s Solution: Bringing Multispectral to Everyday Devices
Spectricity’s technology combines laboratory-grade spectral precision with scalable, compact integration.
The S1 Multispectral Image Sensor features 15 channels in the visible spectrum with an average 34 nm FWHM bandwidth and 864 × 648 SVGA spatial resolution. Spectricity uses its patented FP Precision Filter Technology, based on Fabry–Pérot interference filters, which selectively transmit specific wavelengths through precisely engineered layered structures. This design delivers exceptional spectral and spatial performance in a miniature form factor, combining long-term stability with chip-scale manufacturability. It enables cost-efficient, high-performance multispectral imaging for smartphones, wearables, and measurement instruments.
Spectricity’s S1 product line, shown in Figure 2, is designed for easy integration and application development:
- S1 VIS Multispectral Image Sensor: Miniaturized and mass-manufacturable image sensor with 15 channels across 400–700 nm visible range
- S1-M VIS Camera Module: Compact module with custom optics and onboard memory for calibrated spectral capture
- S1-A VIS Accessory Device: Portable USB-connected device providing plug-and-play multispectral imaging
- S1-EVK2b Evaluation Kit: Dual-camera system featuring the S1-M and an RGB sensor with NVIDIA Jetson for development
Conclusion
Both multispectral and hyperspectral imaging expand how we see and measure light, but they serve different roles in modern imaging applications.
Hyperspectral imaging (HSI) provides unparalleled spectral precision for research, material analysis, and remote sensing, while multispectral imaging (MSI) delivers compact, efficient, and scalable performance for embedded, high-volume devices. MSI’s snapshot imaging capability allows simultaneous capture of multiple bands in real time, making it ideal for applications such as smartphones, consumer electronics, robotics, and industrial vision systems.
Before choosing between HSI and MSI, consider your project’s needs in spectral detail, spatial resolution, data size, processing demands, integration limits, and budget to ensure the right balance of performance, scalability, and cost.
FAQs
2. Why is snapshot multispectral imaging ideal for mobile and embedded systems?
<p style="text-align: justify;">Snapshot MSI captures multiple wavelength bands simultaneously without scanning, allowing real-time performance and lower computational demand. This makes it highly suitable for devices that require compact design, low power consumption, and immediate results, such as smartphones, wearables, robotics, and portable medical or color measurement instruments.</p>
3. Does hyperspectral imaging always provide higher accuracy?
Not necessarily. HSI delivers very high spectral resolution and can reveal subtle spectral differences, but it requires large datasets and complex processing. MSI provides sufficient accuracy for many applications while remaining easier to integrate and operate. The choice ultimately depends on the level of spectral precision the application requires.
4. What are the main factors to consider when choosing between MSI and HSI?
Key considerations include required spectral resolution, spatial resolution, data volume, processing capability, system size, and budget. For applications prioritizing portability and real-time imaging, MSI is typically more practical, while HSI suits research and analytical work that demands fine spectral detail.
5. What future trends are shaping multispectral and hyperspectral imaging?
Both technologies are advancing, but their focuses differ. Hyperspectral imaging is evolving toward faster data acquisition, improved processing algorithms, and AI-driven spectral analysis to handle large datasets more efficiently. Multispectral imaging, meanwhile, is moving toward broader adoption in compact, networked, and embedded devices through innovations in miniaturization, integration, and real-time processing on edge-AI devices. As hardware and computation improve, both MSI and HSI are becoming more accessible across research, industrial, and consumer applications.
More Resources
- What is Multispectral Imaging (MSI)?
- Spectricity Unveils S1-A Accessory Device for Plug-n-Play Spectral Imaging on Mobile Platforms
Discover how Spectricity’s multispectral imaging solutions can transform your next-generation device. Learn more about our products or contact us for a demo. Follow Spectricity’s LinkedIn account for more information.