Optical remote sensing captures images of the earth’s surface by detecting sun energy reflected from nearby, near, and short-wave infrared sensors. Certain materials reflect and absorb light differently at different wavelengths. So, it is possible to differentiate the targets in the remotely sensed images based on their spectral reflectance properties. Optical remote sensing systems can be categorized into different groups according to the number of spectral bands utilized during the imaging process. According to this categorization, the main difference between multispectral and superspectral is the number of bands and how narrow the bands are.
Typically, 3 to 10 bands are used to describe multispectral imaging. There is a clear title for each band. Multispectral imaging is a technology that captures images at specific frequencies across the electromagnetic spectrum, rather than just the visible spectrum. This allows for the detection of features and properties that are not visible to the naked eye. Multispectral imaging has applications in fields such as remote sensing, astronomy, and medical and forensic imaging. In this type of imaging, the sensor is a multichannel detector with a few spectral bands. Each channel is sensitive to radiation within a narrow wavelength band. The resulting image is a multilayer image which contains both the brightness and spectral (color) information of the targets being observed.
Some wavelengths are visible to the eye and some are not.
The colors as we see are defined within this range of wavelengths.
Superspectral is a term used to describe a type of sensor that is capable of capturing more than the three primary colors of the visible spectrum (red, green, and blue) that traditional cameras capture. Superspectral sensors are able to capture additional spectral bands, which can provide more information about the objects being imaged. A superspectral imaging sensor has many more spectral channels (typically >10) than a multispectral sensor. The bands have narrower bandwidths, enabling the finer spectral characteristics of the targets to be captured by the sensor. This technology has applications in fields such as agriculture, environmental monitoring, and medical and forensic imaging. Superspectral sensors are able to capture wavelengths of light that are beyond the range of human vision, such as ultraviolet and infrared radiation. This allows them to detect patterns and features that are not visible to the naked eye, which can be useful in a variety of applications like mentioned.
Multispectral and Superspectral imaging can also be used in forensic investigations. By analyzing the spectral properties of various materials, such as bloodstains, fibers, and gunshot residue, forensic scientists can identify and analyze evidence that might be missed with traditional techniques. This can help to solve crimes and provide more accurate evidence in legal proceedings.
