VNIR to NIR hyperspectral imaging systems for microscopy, lab, field, and tower-mounted applications
The SOC710 hyperspectral camera stands out with its unique internal scanning design, making it the most versatile hyperspectral imaging system available. Its flexible setup allows for seamless integration as a lab benchtop system or attachment to a tripod, boom, or tower for field measurements, eliminating the need for specialized scanning hardware. Additionally, the c-mount objective lens offers many field-of-view options and can be easily attached to commercial microscopes for hyperspectral microscopy. The SOC710 is the ideal hyperspectral imager for any lab’s current and future research needs.
Time Lapse Capability
Automated hyperspectral data acquisition capability
Watch To Learn More About SOC710 Hyperspectral Cameras
HIGH PERFORMANCE HYPERSPECTRAL IMAGING
Hyperspectral imaging systems for microscope, lab, field, and tower-mounted applications
High Spectral Resolution
Our decades of experience with spectral imaging instruments have contributed to the design of the SOC710 Series, creating systems with high spatial and spectral resolutions, high signal-to-noise, and very low optical distortions and stray light. Our systems are designed around the latest spectral and sensor technologies to balance performance, reliability, and affordability.
Unique Internal Scanning Design
The SOC710 instruments are complete hyperspectral imaging systems. No additional scanning equipment is needed. The SOC710’s unique internal scanning mechanism is ideal for lab and field measurements, and tower-mounted configurations and is plug-and-play for microscopy applications.
Interchangeable C-Mount Lenses
SOC710 Series cameras can use a wide range of lens options enabling the system to adapt to different scales, from close-up inspections to broad landscape remote sensing.
Superior Technical Support
Surface Optics prides itself on providing strong technical support for our hyperspectral customers. Our expert team assists with training, equipment setup, troubleshooting, data acquisition, and data analysis.
710 Series Models
710-E
400 nm – 1000 nm
710-sCMOS
400 nm – 1000 nm
710-SWIR
900 nm – 1700 nm
More Information
710-E |
710-sCMOS |
710-SWIR |
|
|---|---|---|---|
Spectral Range (nm) |
400 – 1000 |
400 – 1000 |
900 – 1700 |
Spectral Channels |
260 |
256 |
288 |
Spectral Bandwidth (nm) |
2.31 |
2.34 |
2.78 |
Spectral Resolution (FWHM) (nm) |
|||
Spatial Pixels |
704 |
2048 |
512 |
Aperture |
f/2.4 |
f/2.4 |
f/2.0 |
Pixel Size (µm) |
5.86 |
6.5 |
15 |
Noise Equivalent Spectral Radiance (NESR) (W/m²-sr-nm) |
1.258E-03 @ 550nm |
2.877E-03 @ 550nm |
1.258E-03 @ 550nm |
Bit Depth |
12 |
16 |
12 |
Stray Light |
< 0.5% |
< 0.5% |
< 0.5% |
Objective Lens |
C-Mount / NIR corrected |
C-Mount / NIR corrected |
C-Mount / SWIR corrected |
Max Frame Rate (fps) |
166 |
160 |
107 |
Interface |
USB 2.0 |
USB 3.0 |
USB 2.0 |
Weight (kg / lbs) |
3.85 / 8.5 |
3.85 / 8.5 lbs |
5.44 / 12.0 |
Dimensions (cm) |
12.7 x 20.3 x 28.0 |
12.7 x 20.3 x 28.0 |
13.0 x 20.0 x 27.0 |
Power (V) |
12 DC / 100-240 AC |
12 DC / 100-240 AC |
12 DC / 100-240 AC |
For accessories information email: contact@surfaceoptics.com
Li, H., Sun, L., Jin, X., Feng, G., Zhang, L., Bai, H., & Wang, Z. (2025). Research on variety identification of common bean seeds based on hyperspectral and deep learning. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 326, 125212. https://doi.org/10.1016/j.saa.2024.125212
Hu, X., Ma, P., He, Y., Guo, J., Li, Z., Li, G., Zhao, J., & Liu, M. (2023). Nondestructive and rapid detection of foreign materials in wolfberry by hyperspectral imaging combining with chemometrics. Vibrational Spectroscopy, 128, 103578. https://doi.org/10.1016/j.vibspec.2023.103578
Pang, L., Wang, J., Men, S., Yan, L., & Xiao, J. (2021). Hyperspectral imaging coupled with multivariate methods for seed vitality estimation and forecast for Quercus variabilis. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 245, 118888. https://doi.org/10.1016/j.saa.2020.118888
Zhu, X., & Li, G. (2019). Rapid detection and visualization of slight bruise on apples using hyperspectral imaging. International Journal of Food Properties, 22 (1), 1709–1719. https://doi.org/10.1080/10942912.2019.1669638
