Like most technologies, hyperspectral imaging (or HSI for short) has its own jargon and terminology. Here we provide key term definitions to help you better understand the language of hyperspectral imaging.
First, we will discuss a few concepts that will make the terminology clearer.
Conventional color imaging records the light spectrum from an object in three broad channels, typically red, green, and blue (RGB). This type of imaging effectively provides us with a bar chart approximation of the actual light spectrum. By comparison, hyperspectral imaging records the spectrum in many tens to over a hundred distinct channels that match very closely the true distribution of wavelengths.
The human eye is basically a 3-color channel device that is sensitive to wavelengths from 400 to 700 nm. Hyperspectral imagers can detect spectral ranges that extend beyond that of the human eye, so they can see what our eyes cannot.
All Resonon’s hyperspectral cameras are line-scan imagers. Line-scan imaging (sometimes called push broom imaging) is the process of collecting one line of data at a time. Figure 2. Shows a simplified schematic of the process. The full spectrum for each pixel in the line is collected simultaneously. This line of pixels is the cross-track spatial dimension of the datacube. Either the camera or the object being scanned translates or rotates, building up the along-track spatial dimension of the datacube.
Figure 2: Schematic of a line-scan hyperspectral imaging system
Range: The range of
electro-magnetic wavelengths (e.g., light) in nanometers (nm) over which the
instrument collects data. For reference, visible wavelengths span from approximately
400 nm to 700 nm. See Figure 3.
Figure 3. Schematic showing several spectral ranges and the corresponding wavelengths
- Datacube: The complete data associated with a hyperspectral scan including the light intensity at each wavelength for each pixel. Like color (RGB) images, datacubes have two spatial dimensions and one spectral dimension. See Figure 4. However, in a hyperspectral datacube, the spectral dimension contains light intensity for many channels (as opposed to only three colors in RGB images).
Figure 4. Representation of a datacube for a flower
- Spatial Channels: The Spatial Channels are the number of pixels along the long dimension of the line-scan line, also called the cross-track spatial dimension. See Figure 4.
- Spectral Channels: The number of contiguous bands the instrument measures across the Spectral Range. Most cameras you experience day-to-day, like the camera in your cell phone, are color cameras that only have three spectral channels (Red, Green, and Blue), as opposed to the hundreds of spectral channels of a hyperspectral imager.
- Spectral Resolution: The narrowest spectral feature, usually specified in nanometers (nm), you can measure with the instrument.
- Spectral Sampling: The Spectral Range divided by the number of Spectral Pixels. The Spectral Sampling is often narrower than the Spectral Resolution. The reason for this is that the optics blur the signal from a single point to a size larger than a pixel.
- Max. Frame Rate: The maximum line-scan rate of the imager, usually specified in Frames Per Second (FPS). This is how quickly successive lines of data can be collected, not the frame rate for acquiring an entire 2-dimensional image of a scene or object, which depends on the number of lines contained within the scan.
- Bit Depth: The bit level of the data recorded for each channel. For example, a Bit Depth of 12 means 2^12, or 4096, discrete values to record signal values for each spectral channel.
- f/# (“f-number”): The f/# is a measure of the optical aperture of the hyperspectral system and is a quantity that is needed to determine how much light is collected. f/# for a hyperspectral imager means the same as it does for a conventional camera.
- Binning: The process by which multiple pixels are lumped together into a single spatial or spectral channel to increase signal, and signal-to-noise ratio. The tradeoff is a loss in spatial or spectral resolution.
- Pixel Size: The center-to-center physical distance between pixels on the sensor array.
- Pixel Well Depth: The maximum number of electrons a pixel can store before saturating.
- Slit Width: The width of the slit through which light passes as it enters the hyperspectral imager.
- Spectrometer Magnification: The ratio between the slit image width on the hyperspectral sensor’s array and the physical slit width.
- Field of View (FOV): The Field of View defines the angular range imaged along the long dimension of the line imaged by the hyperspectral imager, reported in units of degrees. The FOV of a hyperspectral imager can be changed by using a different objective lens.
- Instantaneous Field of View (IFOV): The Instantaneous Field of View defines the narrow angular dimension of the line imaged by the hyperspectral imager, reported in units of milli-radians. The IFOV is also changed when a different objective lens is used on the hyperspectral camera.
Figure 5. Schematic showing the Field of View (FOV) and Instantaneous Field of View (IFOV) of a line-scan imager
Airborne Remote Sensing Systems Specific Acronyms
- GNSS (Global Navigation Satellite
- GPS (Global Positioning System): US
term for GNSS.
- RTK (Real Time Kinematic position): Global
Positioning System (GPS) accuracy is limited to a few meters due to
atmospheric physics, so a common solution is to use an ‘RTK base station’
positioned at a known location to estimate the local atmospheric error and
broadcast a correction to the mobile/airborne GPS. This brings the positioning
error down to the centimeter level!
- IMU (Inertial Measurement Unit): A
sensor that measures accelerations, angles relative to gravity, and magnetic
heading. When integrated with a GNSS or GPS, you get geospatial location
(attitude and longitude) of the aircraft as well was the direction the imager
is pointing. This information allows us to create accurate maps with the
- SWaP (Size, Weight, and Power): General
parameters of some electronic systems.
Hyperspectral Imaging with Resonon
Resonon designs and manufactures hyperspectral imaging cameras that accelerate advancements in science and industrial operations. Whether you are pushing the limits of academic knowledge or improving quality on the factory floor, we are here to help you capture and utilize the data that drives new discoveries and enables your success.