Hypercube Waveband Registration
Introduction
Hyperspectral Imaging
Hyperspectral imaging allows us to visualize a vast portion of the electromagnetic spectrum and detect information that would otherwise be invisible to the naked eye. Hyperspectral sensors are able to extend its spectral footprint significantly beyond the visible red, green, and blue bands into the infrared region. The availability of sensor data at a large number of spectral bands generates a three-dimensional hypercube whose levels represent the different spectral bands and whose values at each level represent the sensor-detected light intensity at the corresponding pixel location at that specific band. Analyzing information presented by these additional spectral bands may lead to additional insight on a particular object or scene. For example, different materials have different spectral signatures. The existence of certain material in a scene or an object may be much more evident in a particular waveband than others.
Available Hyperspectral System
Hyperspectral cameras are defined by their spectral and spatial resolutions. The hyperspectral imaging system used to capture data for this project consists of two individual hyperspectral cameras mounted side-by-side. One is responsible for the visible and near-infrared (VNIR) portion of the spectrum and operates in the range of 400 to 1000 nm. The other captures the short-wavelength infrared (SWIR) portion and works in the 900 to 2500 nm range. While there are many obvious advantages of using a hyperspectral imaging system, there are imperfections inherent in the design of the system. In this project, we consider the misregistration (pixel misalignment) between bands within either the VNIR or SWIR camera, as well as misregistration between the two cameras. We make an effort to quantify the extent of the misregistration using the mutual information measure in probability and information theory. In the consideration of misregistration, we also encounter other imperfections in the spectral images, of which we pay particular attention to how noise at certain bands affects the processing of the hyperspectral data.
Methods
- What you did
Results
- What you found
Conclusions
- What it means
References
- HySpex Main Specifications. Norsk Elektro Optikk A/S (NEO).
- Skauli, Torbjorn. Hyperspectral Sensor Technology. Norwegian Defence Research Establishment.
- Viola, Paul A. Alignment by Maximization of Mutual Information. Massachusetts Institute of Technology. 1995.
Appendix I
- Code and Data
Appendix II
- Work partition (if a group project)