Hyperspectral 20 MP Video Camera with a Groundbreaking New Approach
The new hyperspectral video camera ULTRIS is based on light field technology and offers high data quality, flexibility, and speed.
The FireflEYE Q285 was, at the time of its launch, the first hyperspectral camera that could acquire a complete hyperspectral data cube (x, y, λ) with a single image shot. The prism-based sensor technology offered light efficiency of up to 70%. With 125 spectral channels (450 nm to 950 nm) and an image size of 50×50 px, 2500 spectra were recorded simultaneously. However, with just 50×50 px, it is difficult to resolve spatial structures in the image. Therefore, a second image sensor with only one band (panchromatic) was integrated into the camera, imaging the same view with 1000×1000 px.
With this additional information, users can perform a pansharpening of the spectral data that transforms the final data cubes to a maximum size of 1000×1000×125.
Responding to customers’ demand for even higher non-interpolated resolution, Cubert expanded its portfolio with the multispectral ButterflEYE camera, which was based on filter-on-chip technology. The combined model ButterflEYE X2 provides an image resolution of 512×272 px. However, the number of spectral channels decreased to 16 or 25, depending on the sensor type.
During an EPIC (European Photonics Industry Consortium) webinar on Hyperspectral Imaging, Cubert CEO Dr. René Heine provided insights into the new hyperspectral light field camera ULTRIS 20, the technology, and its various application fields.
Fundamentally New Snapshot Technology
Today, the new Cubert ULTRIS breaks new ground as the first HSI camera that is based on light field technology. The camera features an Ultra-HD CMOS sensor with 20 MP, making it the imaging spectrometer with the worldwide highest resolution. During image acquisition, the object is recorded with a multitude of images, each with its own optical bandpass filter with a different center wavelength. This is made possible by combining a continuously variable bandpass filter with a lenslet array. The camera provides a native image resolution of 400×400 px with 100 spectral channels, continuously covering the wavelength range from 450 nm to 850 nm. This means that the previously unheard-of number of 160,000 spectra is acquired simultaneously. The 12-bit sensor of the camera makes it possible to detect minute intensity differences in the spectral content while keeping the noise level very low. The dual GigE camera interface guarantees an image frame rate of 6 Hz.
Looking at the distribution of the spectral channels across their respective wavelength ranges between the three cameras, the improvements become obvious. Due to its prism-based optics, the Q285 has a continuous but non-linear distribution of the channels. The X2 camera additionally suffers from the fact that the distance and position of the spectral channels cannot be accurately determined because of the complicated production process of the filter-on-chips. The channels of the ULTRIS, on the other hand, are spaced equidistantly with a bandwidth (FWHM) of two percent of the center wavelength.
Hyperspectral Cameras IN Comparison
Image comparison of the three hyperspectral cameras FireflEYE Q285, ButterflEYE X2 (dual filter-on-chip), and ULTRIS Q20
For each camera, an RGB image (true color) and two vegetation indices (hNDVI and RedEdge) are shown.
The three cameras (ButterflEYE X2, FireflEYE Q285, and ULTRIS Q20) were installed in the same set-up for a comparison. The exposure time was optimized with the help of a white reference to derive the maximum dynamics. As illumination, a stabilized tungsten light source (50 W) was used with exposure times of 10 ms (FireflEYE Q285), 16 ms (ULTRIS Q20), and 120 ms (ButterflEYE X2). The reflectance properties of the test samples were calculated by subtracting the dark current image from the measurement image and subsequently dividing it by the image of a calibrated 95% white reference (Zenith Lite). The dark current measurement and the white reference were averaged 20 times to achieve good noise reduction.
The measurements, however, were acquired without any averaging or post-processing in order to faithfully represent the inherent noise. The data are presented in their original form without averaging, sharpening, or smoothing to show the true spectral quality of each sensor. Image 1 shows quantities derived from the hyperspectral data cubes. The first line shows typical RGB representations (true color), and the two bottom lines show typical indices that are used for vegetation analysis. Each pixel of the different images represents one spectral curve of the respective sensors.
In the case of the FireflEYE Q285, the low spatial resolution is obvious. The color representation, on the other hand, is very clear, which is also confirmed by the noise-free images of the vegetation indices. The filter-on-chip-based camera X2 has a higher spatial resolution but exhibits the typically high noise level of this sensor. Especially the vegetation indices can only be used after intensive post-processing. The new ULTRIS combines high spatial resolution with low noise levels. Both the image quality and the spectral quality are excellent. The image noise is on a comparable level with the FireflEYE Q285.
Comparison of the spectral quality of the three hyperspectral imaging cameras
For each camera, the spectra of the red, green, and yellow samples are shown along with the respective noise-indicating standard deviation.
The graphs show the spectral signature of three differently colored paper samples for each camera. The spectra of all pixels in a predefined area with homogeneous color were averaged. Since the standard deviation represents the noise equivalent of the sensors, it is used as error bars for each channel. The result clearly shows that the new ULTRIS can easily match the spectral quality of the FireflEYE, even though the ULTRIS has a tremendously higher spatial resolution.
About the Author
Dr. René Heine is the Co-Founder and CEO of Cubert GmbH, a leader in real-time spectral imaging. Since founding the company in 2012, René has been instrumental in shaping Cubert’s technological direction and growth. He holds a Doctor of Physics degree from the University of Ulm, where he graduated magna cum laude, and completed his diploma thesis at Harvard Medical School. René’s deep expertise in physics and his vision for cutting-edge imaging technologies drive Cubert’s innovations and advancements in hyperspectral solutions.
