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.
What is Multispectral Imaging (MSI)?
Beyond the conventional red, green, and blue (RGB) color spectrum captured by normal cameras, a world of hidden information lies waiting to be unveiled. Multispectral Imaging (MSI) is a powerful technology that allows us to visualize this unseen world and reveal useful information. The data extracted can be used to revolutionize diverse fields ranging across precise color matching in industrial applications, in-depth analysis for cosmetics and skin care, agricultural growth and health monitoring, and even advanced diagnostics in medical settings. The technology has existed for many years, but only recently has it become available for a broad audience through affordable snapshot multispectral image sensors.
In this article, we’ll explain what multispectral imaging is, how it works, and its key applications, along with an introduction to how companies develop compact, high-performance snapshot multispectral imaging solutions.
What is Multispectral Imaging?
Multispectral Imaging (MSI) is a technique that captures and analyzes images across multiple, specific wavelength ranges of the electromagnetic spectrum. As seen in Figure 1, compared to many off-the-shelf RGB cameras that only capture red, green, and blue wavelengths, multispectral imaging captures many spectral datapoints for each pixel in an image.
To give a real-world analogy, it’s like seeing through a set of colored sunglasses, each tuned to reveal hidden details. For example, Spectricity’s S1 Multispectral Image Sensor supports operation in 15 independent color channels, covering 400 nm to 700 nm. The richer data allows detailed analysis, identification, and advanced AI algorithm development that could not be achieved with an ordinary RGB camera.
How Multispectral Imaging Works: Technology Explained
Achieving Snapshot Multispectral Imaging
Understanding what multispectral imaging is only tells half the story. It's also essential to delve into the technology behind, and how it evolved —from slow, mechanical systems to fast, compact snapshot solutions.
Traditional methods rely on sequentially modifying incoming light and capturing multiple images to create a composite multispectral image. For example, filter wheel imaging rotates a wheel of narrowband filters, capturing separate images for each filter. Similarly, prisms or gratings split light into multiple wavelengths, requiring mechanical scanning to assemble a full spectral image. These techniques are slow, rely on costly photonic components, and require bulky mechanical assemblies—making them impractical for mobile or handheld applications. Their high cost has also limited adoption for consumer-oriented use cases.
To make multispectral imaging accessible to broader markets, snapshot multispectral imaging is essential. Currently, only two key technologies exist to achieve spectral separation while capturing live images in a tiny format at a low price point: organic color filters and interference filters. Both approaches build on standard CMOS image sensors and apply static optical filters directly at the pixel level. This design trades some spatial resolution for spectral resolution while preserving the speed, cost-effectiveness, and compact form factor of modern camera technology—bringing multispectral imaging to everyday devices.
Organic Color Filters
Organic color filters rely on specially designed dye materials that selectively absorb certain wavelengths, while allowing others to pass through. The absorption spectra can be engineered by chemical synthesis to achieve custom spectral bands needed in multispectral imaging. This kind of filters can be deposited onto sensor surfaces relatively easily, making them cost-effective for some imaging applications.
However, the spectral filter responses of organic color filters are very broad (>100 nm), which requires extensive data processing to extract detailed spectral information, limiting the application for multispectral imaging. Furthermore, consistency and long-term stability remain a challenge, as the organic compounds tend to deteriorate over time. As a result, while organic filters are suitable for basic color separation, they fall short when it comes to advanced multispectral imaging applications.
Interference Filters
Interference filters, such as those based on Fabry–Pérot interferometry, achieve spectral separation through precisely engineered layered structures. By controlling the thickness of these layers, specific wavelength bands can be selectively transmitted while others are blocked.
This approach delivers superior spectral resolution, stability, and higher performance for spectral reconstruction, compared to dye-based filters. It also enables compact and chip-scale integration, making it ideal for high-performance multispectral image sensors for mass production in mobile and consumer electronics.
Spectricity's FP Precision Filter Technology
Spectricity’s Multispectral Image Sensor integrates unique and patented FP Precision Filter Technology in a mosaic pattern on a CMOS image sensor. In Figure 2, Spectricity controls the filter center wavelengths by differentiating the thickness of the layers built on a CMOS image sensor. As a result, each pixel yields a narrowband response. The FP Precision Filter Technology is scalable and adaptable to any image sensor, bringing multispectral imaging to tiny form factors.
Key Applications of Multispectral Imaging
Multispectral imaging (MSI) transcends the limitations of traditional photography by capturing information beyond an RGB camera. This powerful technology has found its niche in a diverse array of fields to unlock hidden information, enabling more informed decisions and deeper understanding across countless applications.
- Color Matching: Accurate color picking with mobile sensing and advanced color correction for AWB
- Food & Agriculture: Monitoring of plant growth and health, food freshness & quality inspection, species sorting
- Medical: Monitoring of wound healing, prevention of diabetic foot ulcers, and skin cancer
- Security and Surveillance: Detecting concealed objects, identifying counterfeit documents, and CCTV monitoring
- Beauty & Health: Accurate skin tone detection, advanced skin analysis with biomarkers, and personalized skin care recommendations
Figure 3 illustrates this application in a skin care scenario. By leveraging Spectricity’s multispectral imaging together with advanced AI algorithms, users receive personalized skin care recommendations, such as skin tone and full biomarker maps, including melanin, blood volume, and skin oxygenation. This makes it easy for users to find their cosmetic match and diagnose skin issues like dark circles under the eyes.
Developing Compact Multispectral Imaging for Mobile Devices
As the potential of mobile multispectral imaging becomes increasingly clear, companies like Spectricity are at the forefront of bringing this technology to everyday devices. Spectricity specializes in developing miniaturized multispectral imaging solutions specifically designed for integration into mobile devices. Spectricity offers the following products, shown in Figure 4.
- S1 Multispectral Image Sensor: World’s first truly miniaturized, mass-manufacturable mobile multispectral image sensor featuring 15-channel high spectral resolution across 400 nm to 700 nm.
- S1-M Camera Module: A compact camera module that includes a specially designed lens and onboard memory for accurate and fully calibrated spectral responses of the S1 sensor.
- S1-EVK2b Evaluation Kit: A dual-camera unit consisting of a co-packaged S1-M multispectral camera module and RGB image sensor together with NVIDIA Jetson computer for application development.
- S1-A Accessory Device: A portable device equipped with the S1-M camera module that pairs seamlessly with mobile devices by connecting via a simple USB interface.
Conclusion: MSI Sensing Beyond What Is Visible
To summarize, multispectral imaging (MSI) moves beyond standard RGB, revealing hidden data by capturing light across specific wavelengths. With the advent of snapshot multispectral imaging, this powerful technology has moved from bulky, expensive systems to compact, cost-effective solutions that fit into mobile devices.
This technology, like Spectricity's miniaturized solutions, integrates unique filter tech onto sensors, providing richer insights for diverse applications. From precise color matching and enhanced security to advanced medical diagnostics and personalized beauty solutions, multispectral imaging is revolutionizing various fields. As mobile multispectral imaging becomes more accessible, it is set to transform everyday devices and empower smarter decisions across a wide spectrum of uses.
FAQs
2. What is the difference between multispectral imaging and RGB imaging?
RGB imaging captures only three broad color channels—red, green, and blue—limiting its ability to detect subtle variations. Multispectral imaging captures 5 to 15 or more spectral bands, enabling more precise color matching and material analysis.
Spectricity’s S1 Multispectral Image Sensor supports 15 independent color channels spanning 400 nm to 700 nm, providing much richer data than standard RGB sensors.
3. What technologies are used for spectral filtering in multispectral imaging?
There are different technologies used to achieve this spectral separation, including organic color filters and interference filters. Organic filters are cost-effective but less precise, while interference filters offer high spectral resolution and stability, ideal for miniaturized, high-performance sensors.
4. What is Fabry–Pérot interference in multispectral imaging?
Fabry–Pérot interference filters use precisely engineered layered structures to selectively transmit specific wavelengths.
Spectricity uses patented FP Precision Filter Technology integrated directly onto CMOS sensors in a mosaic pattern. This enables narrowband spectral capture in extremely compact, mobile-ready designs.
5. What are the applications of multispectral imaging?
Multispectral imaging has diverse applications, including:
- Mobile cameras for accurate color correction
- Cosmetics and skin analysis
- Food quality and agricultural monitoring
- Medical diagnostics
- Security and surveillance
And many more...
6. Why is multispectral imaging important for mobile and consumer electronics?
As mobile devices get smaller and smarter, multispectral imaging enables features like advanced skin analysis, precise color matching, and improved AI capabilities — transforming user experiences in beauty, health, photography, and more.
More Resources
- Spectricity Demonstrates AI-Powered Skin Analysis with Multispectral Technology on Mobile Devices
- 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 [email protected] for a demo. Follow Spectricity's LinkedIn and WeChat (scan QR Code: spectricitychina) accounts for more information.
